quantitative research about food industry in the philippines

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Article Contents

1. introduction, 2. background, 3. conceptual model and empirical framework, 5. results and discussion, 6. conclusions and policy implications, acknowledgements, conflict of interest, data availability statement.

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Estimating food demand and the impact of market shocks on food expenditures: The case for the Philippines and missing price data

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Harold Glenn Valera, Joaquin Mayorga, Valerien O Pede, Ashok K Mishra, Estimating food demand and the impact of market shocks on food expenditures: The case for the Philippines and missing price data, Q Open , Volume 2, Issue 2, 2022, qoac030, https://doi.org/10.1093/qopen/qoac030

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This study uses the Quadratic Almost Ideal Demand System to estimate food demand among Filipino households. Our study uses the recently released 2018 Family Income and Expenditure Survey and the Stone-Lewbel price index in the absence of price data on food groups. Results show that demand for rice with respect to prices and expenditures is relatively inelastic compared with that for other food groups. The income elasticity for rice is inelastic (0.26), slightly higher than the income elasticity for sugar. Demand for rice is generally less elastic for higher-income Filipinos and families residing in urban areas than for their counterparts. The findings reveal that, in the short term, a 15 per cent decrease in income or a 20 per cent increase in rice prices induces families to spend more of their income on rice at the expense of other cereals, meat, fish, and other food groups. Income and rice price shocks have differential impacts on low-income and high-income Filipino families. Policymakers may be able to moderate the food price impacts of market shocks through targeted interventions and programs that improve the accessibility to and availability of quality agri-fishery products.

The rice sector plays a significant role in Philippine agriculture and the economy. As of 2018, about 10 million farmers and family members—representing 22 per cent of the rural population—depended on growing rice for their livelihood. Recent data show that annual rice production fell to 114.69 kg per capita ( PSA, 2020 ). The per capita output was slightly lower (2.7 per cent) than the record set in 2018. Rice is the staple food for 109.04 million Filipinos ( PSA, 2021 ), who consume an average of about 110 kg of rice per capita per year ( PSA, 2018 ). Rice accounts for more than a third of the average calorie intake of Filipinos. In addition, rice is a major food expense, accounting for 13.1 per cent of total household spending and a third of total food consumption. Thus, rice in the Philippines is a highly political crop and a sensitive issue for policymakers regarding food prices and security.

The 2018 Family Income and Expenditure Survey (FIES) revealed that Filipinos’ average annual income increased by about 17 per cent, from 268,000 pesos in 2015 to 313,000 pesos in 2018. Average family income also increased in all deciles. On the other hand, the average family expenditures during the same period increased by about 11 per cent, from 216,000 pesos to 239,000 pesos. In 2018, 42.6 per cent of the average Filipino family's spending was on food, an increase of 0.8 percentage points from 2015 (41.8 per cent). Of the above proportion, 33.6 per cent was spent on food consumed at home and only 9.0 per cent was spent on food outside the home. Among the food items consumed at home, bread, and cereals had the highest share of food expenditures (11.0 per cent), followed by meat (5.7 per cent) and fish and seafood (5.0 per cent) ( PSA, 2020 ). A 0.7 per cent share of expenditures was for oils and fat. Unlike the income pattern observed in deciles, for families in the bottom 30 per cent income group, 58.2 per cent of their total expenditures went for food compared with 39.5 per cent for families in the upper 70 per cent income group.

Price and income shocks affect families in various income groups differently regarding food expenditures (or food consumption). For instance, for the early 2000s, Ivanic and Martin (2008) noted that price shocks in low-income countries negatively affected poverty rates. The authors stated that rice prices increased by 25 per cent, leading to higher poverty rates in rice-dependent countries. Other studies have also investigated the causes of higher food prices and their impact on household welfare ( Dewbre et al., 2008 ; Coxhead et al., 2012 ; Minot and Dewina, 2015 ). In addition, Valera, Balié, and Magrini (2022) recently noted that rice price shocks have a higher inflationary effect than fuel prices and remittance earnings. Thus, the food security of millions of Filipinos is affected by inflation and the rise in commodity prices. Populations across developing and emerging economies also experience income shocks. These income shocks can arise from natural disasters, for example, flooding, droughts, hurricanes, and typhoons ( Samphantharak, 2014 ; Alano and Lee, 2016 ). The authors found that droughts and typhoons decrease national income in the short and long term—about a 2.3 per cent decrease in gross domestic product (GDP). Additionally, in their study, Tanaka, Ibrahim, and Lagrine (2021) found that although large-scale natural disasters hurt real GDP, the effect of the shock persists for a more extended period in the Philippines than in China, India, and Thailand. The Organization of Economic Co-operation and Development (OECD) reports used income and price shocks to estimate household food insecurity ( OECD, 2015 , AAAAAA 2017 ). A related measure that captures the components of food security is the self-sufficiency ratio (SSR), which is the share of production compared with utilization ( Clapp, 2017 ). The ratio indicates how much a commodity's supply is from domestic production. The higher the SSR, the greater the self-sufficiency. 1 Interestingly, in 2019, the SSR for rice dropped to 79.8 per cent from 86.7 per cent in 2018, implying a rice shortage and thus more imports from world markets ( PSA, 2020 ). In other words, the Philippines imported about 20.2 per cent of its domestic rice supply.

Given rice's budgetary and nutritional importance in the well-being of Filipinos, a further understanding of rice demand behavior would provide valuable information regarding food security, income stabilization, and trade policies. Changes in income or relative prices culminate in shifting purchasing patterns, and changes in these factors can lead to a healthier or more malnourished rural population. Thus, information on food demand behavior is crucial in analyzing the effects of different policies and, in turn, in providing recommendations for planning, designing, and implementing government programs that will help improve Filipinos’ food supply and nutritional status.

Our study examines the influence of income, relative prices, and relevant socioeconomic factors on food purchasing behavior, in total and by primary food categories, among Filipino households. The study uses the Quadratic Almost Ideal Demand System (QUAIDS) and recently collected 2018 FIES that collected detailed information on expenditure patterns among Filipino families. In 2019, the Philippines shifted to a liberalized rice trading regime with the Rice Tariffication Law (RTL). Thus, the findings from our study provide a better understanding of the potential effects of future price and income shocks on rice demand. Second, the study offers complementary information to enrich the Philippine Rice Industry Roadmap 2030 (a guide toward achieving rice security—increasing yields, reducing costs, enhancing resiliency, and ensuring safety and nutrition 2 ) in estimating the country's rice demand in rural and urban locations and income of consumer types and improving the quality of policy recommendations in food security and nutritional programs. Finally, another crucial contribution of our study is in providing policymakers with an up-to-date analysis to quantify the effects of various market shocks on consumer food expenditures. 3 Although considerable literature explores food demand estimation for the Philippines, we offer a first study that considers a two-stage budgeting process in food demand instead of treating demand for food commodities in a one-step budgeting process. The household determines the share of income devoted to food in the first step. Based on the outcome of this first stage, the second stage determines how to allocate food expenditures across the different food categories.

The article is structured as follows. The following section discusses the literature on food demand estimation for the Philippines. The third section describes the conceptual framework and empirical methodology. The fourth section describes the data and the fifth section presents the results. The final section concludes and elaborates on policy implications.

Several studies have investigated food demand in the Philippines. In the late 1980s, Quisumbing et al., (1988) used 1978 and 1982 household surveys collected by the Food and Nutrition Research Institute. The study was the first to estimate the demand elasticities of food and non-food items. The study reported disaggregate demand parameters for food subgroups that accounted for location and occupation when assessing food consumption. In the early 1990s, Bouis (1990) estimated the food demand elasticity for urban and rural Filipinos. The author used 1978 and 1982 household surveys to find that meats have higher own-price and income elasticities. In contrast, Bouis (1990) found that maize had a negative income elasticity for rural and urban families. In addition, the author predicted changes in the consumption levels of food items 4 and overall calorie intakes. The author concluded that lower real wages and rising cereal prices 5 would increase malnutrition.

Two years later, Bouis, Haddad, and Kennedy (1992) compared calorie-income elasticities for Kenya and the Philippines. The authors estimated calorie intake and calorie availability for both countries. For the Philippines, our focus in this study is that the authors found that calorie intake and availability are higher for more affluent families for most food items but not for maize. The authors argue that wealthy families buy extra food for guests and workers. Using household survey data from 1985,1988, and 1991, the FIES, and the Almost Ideal Demand System (AIDS), Balisacan (1994) studied food demand by Filipinos. The authors found that most food items (maize, rice, other cereals, dairy and meat, fruits and vegetables, and other foods) were income-inelastic (about 0.1) and did not change with income levels. Balisacan (1994) concluded that although food price responses vary by income group and household location, the variation was not as large as reported in the media.

In the early 21st century, Mutuc, Pan, and Rejesus (2007) , using 2000 FIES data and the QUAIDS, estimated expenditure elasticities for 11 vegetable types 6 in the Philippines. The authors found significant expenditure elasticities between urban and rural residents. However, the authors did not find significant differences in own-price and cross-price elasticities between urban and rural residents. In a recent study, Fuji (2016) compared food demand in the urban populations of the Philippines and China. Using six rounds of FIES data (1988,1991, 1994, 2000, 2003, and 2006), the author found that, from 1998 to 2006, Filipinos’ diet essentially became more westernized. Additionally, urban Filipinos’ demand for meat, vegetables, and fruits was similar to that of the Chinese urban population. Using the 2008–2009 Survey of Food Demand for Agricultural Commodities and Linear Approximate Almost Ideal Demand System (LA/AIDS), Sombilla, Lantican, and Quilloy (2011) estimated rice demand for Filipinos. The authors noted that rice demand was inelastic to total food expenditure, income, and own-price, especially for rural poor Filipinos.

Finally, Dizon and Wang (2019) used 2015 FIES data in estimating own-price and cross-price food demand elasticities to simulate the impact of the rice tariffication policy, which has abandoned quantitative restrictions on rice imports since the promulgation of the RTL in February 2019. The authors highlighted that the corresponding expected decline in rice prices following the rice tariffication policy would increase rice consumption and that of other food groups, with potential for increased diet diversity. In a recent study, Balié, Minot, and Valera (2021) , using the IRRI Global Rice Model, simulated the RTL on the domestic price of rice. The authors found that the RTL decreased consumer and producer rice prices, thus affecting the production and consumption of rice. Rice farmers who were net sellers were negatively affected, although overall the RTL reduced poverty.

The QUAIDS is an extension of the now-famous AIDS proposed initially by Deaton and Muellbauer (1980) . QUAIDS is quadratic in expenditures, more flexible than the AIDS, and allows demand curves to be non-linear in the logarithm of expenditures, thus exhibiting non-linear Engel curves. 7 Specifically, QUAIDS allows a good to be both a luxury item and a necessity good at the two ends of the income distribution ( Banks, Blundell, and Lewbel, 1997 ). Several studies have used the QUAIDS modeling approach (initially proposed by Banks, Blundell, and Lewbel, 1997 ) to estimate broad food demand in developed and developing countries. Studies in developing countries of interest to us in this study are Hoang (2018) for households in Vietnam; Khanal, Mishra, and Keithly (2016) for rural households in southern India; Boysen (2012) for Uganda; Meenakshi and Ray (1999) for Indian families; and Obayelu et al., (2009) and Fashogbon and Oni (2013) for Nigerian households. Other studies include Ecker and Qaim (2011) , who study food and nutrient demand in Malawi. Two studies ( Gould and Villarreal, 2006 ; Zheng and Henneberry, 2010 ) investigated food demand in urban China. Studies in South and Southeast Asia include, for example, Garcia et al., (2005) , Tey et al., (2008) , and Pangaribowo and Tsegai (2011) , who estimated fish demand in the Philippines, rice demand in Malaysia, and food demand in Indonesia, respectively.

Interestingly, a series of studies estimated food demand projections using QUAIDS for Ethiopia ( Tafere et al., 2011 ), Bangladesh ( Ganesh-Kumar et al., 2012b ), and India ( Ganesh-Kumar et al., 2012a ). Food demand studies using QUAIDS also include Vietnam ( Hoang, 2018 ), India ( Khanal, Mishra, and Keithly, 2016 ), and China ( Fashogbon and Oni, 2013 ). The above studies use Ray's (1983) and Poi's (2012) approach to include differences in demographic factors across households when analyzing food and non-food expenditures in a complete demand system. Recent studies using the QUAIDS model are Law, Fraser, and Piracha (2020) and Hussein, Law, and Fraser (2021) . For instance, Law, Fraser, and Piracha (2020) used the QUAIDS model to estimate the combined demand elasticities for cereals to assess changes in the food preferences of Indian households. Hussein. Law, and Fraser (2021) used the World Bank's 2018 Somalia High Frequency household survey data to show the effects of income shocks (civil war in Somalia) on food consumption elasticities (expenditure, own- and cross-price elasticities for animal products).

The above studies, in general, support the superiority of the QUAIDS model compared with the AIDS model when estimating food expenditures, by category, in a complete demand system. 8

Recall that the QUAIDS model accounts for differences in socioeconomic conditions across households by augmenting demographic and household-specific variables (e.g. household size) using the method proposed by Ray (1983) and Poi (2012) . Therefore, our study employs the QUAIDS method for estimating food demand among the Filipino population. We assume weak separability in the household's two-stage budgeting process ( Boysen, 2012 ). In the first stage, the family decides the percentage of the total budget allocated to food. In the second stage, the household allocates the food budget among different food categories. 9 Note that elasticities contingent on exogenous total group expenditure in the demand system may be inappropriate when assuming a two-stage allocation process. Our study overcomes the limitation of single-stage and conditional elasticities by computing appropriate unconditional elasticities. The unconditional elasticities from the demand model are derived following Edgerton (1993 ; 1997 ) and Carpentier and Guyomard (2001) .

3.1. First-stage: expenditure share of food

3.2. second-stage demand system.

Our study uses the 2018 FIES. 15 The FIES is a nationwide survey of households in the Philippines. The first FIES was conducted in 1957. The Philippine Statistics Authority (PSA) gathers family income and expenditure data. The 2018 FIES was the first to use and interview a sample of 170,917 households, which was deemed sufficient to provide reliable estimates of income and expenditure at the national, regional, provincial, and highly urbanized cities (HUC) levels. The 2018 FIES used the 2013 Master Sample sampling design. A total of 2,695 data items were included in the 2018 FIES questionnaire. 16 The sample households covered in the survey were interviewed in July 2018.

The survey reports total expenditures on food and non-food items. Unfortunately, the 2018 FIES data released by the PSA lack quantity and unit prices for the goods the families consumed.

Total expenditures are the sum of all consumption expenditures. Data cleaning and missing information resulted in 147,717 families for analysis in our study. Appendix  Table A2 shows the average socioeconomic and demographic attributes of the families in the 2018 FIES. The average age of the household head (HH) was 48, 84 per cent reported being married, and 86 per cent were employed. The average family size was 4.6 persons per household and 10 per cent of the sampled households lived in poverty. All food items consumed by families are aggregated into nine categories. These categories are (1) RICE (well-milled, regular, National Food Authority, and other); (2) OTHER CRLS (maize and other cereals—maize, flour, cereal preparation, bread, pasta, and other bakery products); (3) MEAT (beef, chicken, goat, pork, preserved meats); (4) FISH (fresh, dried/smoked, preserved, and seafood); (5) FRUIT (fresh, dried, nuts, preserved, and others); (6) VEGE (vegetables, tubers, preserved, and products of tubers); (7) SUGAR (centrifugal, muscovado, refined brown sugar, and others); (8) DRINKS (soft drinks, mineral, fruit juice, concentrates, and other non-alcoholic beverages); and (9) MISC (milk and others).

We divided the sample into three income terciles (low, middle, and high) and two regional categories (rural and urban). The latter two categories are based on the location of the surveyed households.  Table 1 shows the average budget shares and annual income (expenditures) per capita of each selected food group for the sample, income terciles, and urban and rural families.  Table 1 reveals that low-income households spent more than 55 per cent of their total income buying food. The average family spent nearly 42 per cent of its total income purchasing food and food items.

Food expenditure share ( per cent) by income levels and regions, Philippines, 2018.

Source : 2018 FIES. Philippines Statistical Authority. https://psa.gov.ph/tags/family-income-and-expenditure-survey

Exchange rate USD 1 = PHP 52.41 (Philippine pesos). Food groups: RICE = rice (well-milled, regular, National Food Authority (NFA), and other); OTHER CRLS = maize and other cereals (maize, flour, cereal preparation, bread, pasta, and other bakery products); MEAT = beef, chicken, goat, pork, and preserved; FISH = fresh, dried/smoked, preserved, and seafood; FRUIT = fresh, dried, nuts, preserved, and others; VEGE = vegetables, tubers, preserved, and products of tubers; SUGAR = centrifugal, muscovado, refined brown sugar, and others; DRINKS = soft drinks, mineral, fruit juice, concentrates, and other non-alcoholic beverages; MISC = milk and others.

Table 2 presents the estimates of uncompensated price elasticity, expenditure, and income elasticity.  Table 2 shows that nine food items’ estimates of own-price elasticity (the percentage change in the quantity of food items demanded due to a percentage change in price) are negative and statistically significant at the 1 per cent level of significance. On the one hand,  Table 2 also shows that demand for other cereals, meat, fish, fruit, vegetables, and miscellaneous food groups is elastic. On the other hand, demand for rice, sugar, and drinks food groups is inelastic ( Table 2 ). Cross-price elasticities are consistent and in both directions. Our finding is consistent with Hoang (2018) in her study of Vietnamese food demand.  Table 2 shows that rice, the main food item for Filipinos, complements four other food groups, but rice is a substitute for other cereals, fish, and miscellaneous food groups (milk and others). Similarly, the meat group complements seven other food groups but not other cereals and miscellaneous food. The miscellaneous food group is a substitute for all other food groups. Finally, the fruit food group is substitutable with the other cereals, fish, vegetables, and miscellaneous food groups.

Uncompensated price, expenditure, and income elasticities, Philippines, 2018.

Source: Authors’ computation using FIES 2018 https://psa.gov.ph/tags/family-income-and-expenditure-survey . Numbers in parentheses denote standard errors.

Notes: ***, **, * denote significance at 1 per cent, 5 per cent, and 10 per cent levels, respectively.

Demand for rice is near unitary elastic (−0.93) to change in rice prices compared with that for other food groups, with own-price elasticity ranging from −1.67 (drinks) to −1.00 (meats) and to −1.67 (miscellaneous food group). Demand is less elastic for the sugar and drinks food groups, with own-price elasticity of −0.71 for sugar and −0.70 for drinks. Our estimate is consistent with Quisumbing (1986) , who found an elastic price elasticity of demand for rice in the Philippines. Specifically, our estimates are lower, in absolute terms, than those of Quisumbing (1986) , who discovered an own-price elasticity of rice demand from −1.44 to −1.00, depending on the income group. However, our estimate is closer to that of Vu (2009) , who, using the Vietnam Household Living Standard Survey (VHLSS), found an own-price elasticity of demand for rice of −0.8 for Vietnamese households. Our estimates are also closer to the own-price elasticity estimates (−0.6) obtained by Gibson and Kim (2013) , who analyzed 2010 VHLSS data.

However, our own-price elasticity of demand for rice estimate is about two times larger, in absolute terms, than that obtained by Hoang (2018) using 2010 VHLSS data (−0.47). It should be noted that Hoang's rice food group included white rice, sticky rice, rice noodles, and bun . However, several reasons could explain the higher own-price elasticity. First, the higher own-price elasticity for rice could be due to our use of prices at the provincial level. Second, our study's rice group comprises several rice types, including well-milled, regular, National Food Authority, and others. At the provincial level, the price of rice is not differentiated by the type of rice. Third, the elastic response of rice to its own price appears to reflect a slight variation in rice prices. A plausible argument for elastic rice demand could be the westernization of the Filipino diet ( Fuji, 2016 ). Fuji (2016) notes that, from 1988 to 2006, Filipinos increased their food budget share for dairy, eggs, and meat. The author notes a decline in the expenditure share of cereals, including rice, during the same period.

Column 11 of  Table 2 reports the expenditure elasticity of demand for all nine food groups. The expenditure elasticity of demand for rice is 0.67, slightly higher than the expenditure elasticity of demand for the sugar food group (0.56). Our expenditure elasticity estimate for rice is nearly twice as large as the estimates obtained by Vu (2009) and Hoang (2018) . In contrast, the expenditure elasticity 17 of demand for other food groups is significantly larger, ranging from 0.76 to 1.25. Finally, the last column of  Table 2 reports the income elasticity of each food group. Estimates show that the income elasticity of each food group decreases by 50 per cent or more compared to expenditure elasticity, suggesting that each food group is a necessary good for changes in consumer income. The income elasticity of the rice group is 0.26 ( Table 2 , last column), suggesting that a 1 per cent increase in household income (expenditures) increases rice demand by 0.26 per cent. The results suggest an inelastic demand for rice with respect to changes in Filipino families’ income. Our estimate is lower in absolute terms than the estimates obtained by Abad et al., (2010) and Lantican, Sombilla, and Quilloy (2013) . The miscellaneous food group (0.47) and meat food group (about 0.45) have the highest and second-highest income elasticity, followed by drinks (0.37) and other cereals (about 0.35). Interestingly, the sugar food group's income elasticity is the lowest (0.21).

5.1. Income and location disaggregation

Estimates of expenditure and uncompensated price elasticities by income terciles for urban families are provided in Appendix  Table A3 and for rural families in Appendix  Table A4 .  Table 3 presents the estimates for three income groups (low, middle, and high) and urban and rural subsamples. The left panel of  Table 3 shows the expenditure elasticities and the right panel presents the uncompensated own-price elasticities of each food group. As expected,  Table 3 shows that expenditure elasticities are all positive and own-price elasticities are negative for each food group. All estimates are significant at the 1 per cent level of significance. Table 3’s left panel shows that demand for food items, especially rice, tends to be more elastic with respect to expenditures for lower-income and rural households. For instance, the expenditure elasticity of demand for the rice food group is higher (0.78) for low-income families and lower (0.66) for high-income families. Similarly, the expenditure elasticity of demand for the rice food group is 0.65 for rural families and 0.68 for urban families. However, the expenditure elasticity of demand for the other cereals food group is higher (0.96) for high-income families and lower (0.89) for low-income families. The expenditure elasticity of demand for the other cereals food group is 0.98 for rural families and 0.92 for urban families.

Expenditure and uncompensated own-price elasticities for income and regional subsamples, Philippines, 2018.

On the one hand, estimates in  Table 3 (left panel) show that, regardless of income strata and location of families (rural and urban), meat, fish, and miscellaneous food groups appear to be luxury goods (elasticity > 1). On the other hand, estimates in  Table 3 (left panel) reveal that, regardless of income strata and location of families (rural and urban), vegetables and sugar appear to be normal goods (elasticity < 1). Our finding is consistent with Hoang's (2018) and Vu's (2009) results for Vietnamese households. Lastly, drinks are a luxury good for rural households. Interestingly, estimates from our study show that fruits are normal goods for lower- and middle-income Filipino families and luxury goods for high-income urban and rural families. Demand elasticities with respect to prices reveal a pattern that is consistent with expenditure elasticities. For example, the own-price elasticity of rice group demand is decreasing, in absolute terms, with increasing household income. The elasticity of demand is −0.98 for low-income households compared with −0.91 for high-income households. Our estimates follow a similar pattern and are lower in magnitude, in absolute terms, than those of Quisumbing (1986) , who found that the own-price elasticity of demand for rice was −1.45 for lower-income households and about −1.00 for higher-income households. 18 Similarly, the own-price elasticity of rice group demand is higher (−0.93) for rural households than for urban families (−0.91). Our result is consistent with other studies in the literature. For instance, Hoang (2018) , Vu (2009) , and Canh (2008) found the own-price elasticity of rice demand in urban areas to be less elastic than in rural areas.

5.2. Impact of income and price shocks on budget shares

In our study, we model the impacts of two hypothetical scenarios: a 15 per cent decrease in income and a 20 per cent rise in rice prices in the budget share that Filipino families devote to the various food groups. Specifically, we use Hoang's (2018) procedure to estimate the impacts of income and price shocks on budget shares. T able 5 shows the income and price shock results using 2018 FIES data as the baseline. For reasons of space and brevity, we present only the impact on budget shares and quantities and discuss only low-income and high-income households.

Table 4 shows that a 15 per cent reduction in income increases the budget share for rice by 0.1 percentage points for the entire sample and is compensated for by a decrease in the budget share of other meat (−0.1 percentage points) and miscellaneous (−0.1 percentage points) food groups. Interestingly, the impact of a 15 per cent reduction in income on budget shares differs by income group. For low-income families, a 15 per cent reduction in income decreases the budget share for rice by 1.8 percentage points, for other cereals by −0.1 percentage points, for vegetables by −0.1 percentage points, and for sugar by −0.1 percentage points, and is compensated for by an increase in the budget share of meat by 1.0 percentage points, fish by 0.1 percentage points, drinks by 0.2 percentage points, and miscellaneous by 0.7 percentage points. For high-income families, a 15 per cent decrease in income increases the budget share of rice by 2.8 percentage points, thus increasing rice expenditure and purchased quantity by 6.1 per cent. An income decrease also induces a smaller increase in budget share (0.1 to 0.2 percentage points) for non-rice cereals, fish, and sugar. These budget-share increases are offset by decreases in the budget share of meat (−1.2 percentage points), fruit (−0.3 percentage points), drinks (−0.3 percentage points), and miscellaneous (−1.4 percentage points). Our findings for the entire sample and high-income households are qualitatively consistent with those of Hoang (2018) . However, the percentage in the budget share differs because Hoang considered only a 10 per cent reduction in income compared with a 15 per cent reduction in our study of Filipino families.

Impacts of income and price shocks on budget share and per capita quantity, 2018, Philippines.

Source : Authors’ computation using FIES 2018 https://psa.gov.ph/tags/family-income-and-expenditure-survey .

The last panel of  Table 4 shows the impact of a 20 per cent increase in rice prices. The results reveal that a 20 per cent rise in rice prices increases budget shares for rice by 0.1 percentage points and for the miscellaneous food group by 0.9 percentage points for the entire sample. The increase in budget share for rice and the miscellaneous food group is compensated for by a decrease in the meat (−0.4 percentage points), fish (−0.2 percentage points), fruit (−0.1 percentage points), vegetables (−0.2 percentage points), and drinks (−0.1 percentage points) food groups. We also observe that increased rice prices have a differential impact on budget shares by analyzing family income groups. On the one hand, for low-income families,  Table 4 shows that a 20 per cent increase in rice prices decreases the budget share allocated to rice by 1.7 percentage points, vegetables by 0.3 percentage points, and other cereals by 0.2 percentage points. However, a 20 per cent increase in rice prices increases the budget share of the miscellaneous food group by 1.5 percentage points and the drinks food group by 0.1 percentage points. On the other hand, for high-income families, a 20 per cent increase in rice prices increases the budget share of rice by 2.8 percentage points, thus increasing the quantity by 17 per cent. The same price increase will decrease budget shares for meat by 1.6 percentage points, fish by 0.3 percentage points, fruit by 0.5 percentage points, and drinks by 0.3 percentage points. Our estimates for the entire sample and high-income households are consistent, albeit of a different magnitude, with those of Hoang's (2018) study, which considered a 30 per cent increase in rice prices in Vietnam.

Table 4 shows that urban and rural families allocate more of their budgets to rice and reduce expenses on other food items when income shocks occur. For urban families, when income decreases by 15 per cent, the budget share for rice increases by 0.1 percentage points and is primarily compensated for by a decrease in the budget share for miscellaneous food items. In response to decreased income (a 15 per cent reduction), low-income urban Filipino families diminished their budget share for rice by 2.6 percentage points, other cereals by 0.1 percentage points, fish and vegetables by 0.3 percentage points, and sugar by 0.1 percentage points. On the other hand, low-income urban families increased the budget share for meat (1.4 percentage points) and drinks (0.3 percentage points). In response to decreased income, high-income urban families allocated more of their budgets to rice (increasing quantity by 12.7 per cent), other cereals, fish, vegetables, and sugar food items. Perhaps high-income Filipinos have higher saving rates and use savings to buy more food items. For low-income rural families, a 15 per cent reduction in income decreases the budget share for other cereals by 0.1 percentage points. This increases the expenditure share of miscellaneous food items by 0.4 percentage points ( Table 4 ). In response to decreased income, high-income rural families behave similarly to their urban counterparts. Specifically, high-income rural households allocate more of their budgets to rice (by 4.5 percentage points, a 12.8 per cent increase in quantity) and vegetables and sugar (by 0.2 percentage points), and increase the budget share to other cereals by 0.1 percentage points.

In the case of a 20 per cent increase in rice prices, the response is quite different for urban and rural Filipino families. Low-income urban and rural families allocate less of their budgets to rice (a 2.5 percentage points reduction for low-income urban families versus a 1.4 percentage points reduction for low-income rural families). Similarly, low-income urban and rural families allocate less of their budgets to other cereals, both by 0.2 percentage points. Low-income urban families also reduce their budget shares for fish (0.5 percentage points), vegetables (0.2 percentage points), and sugar food items (0.1 percentage points). In response to a 20 per cent increase in rice prices, low-income urban families increase their budget shares for miscellaneous food items (2.3 percentage points), meat (1.1 percentage points), and drinks and fruit (by 0.2 percentage points each). In contrast, high-income urban and rural families allocate more money to rice (1.8 percentage points more for urban families versus 4.4 percentage points more for rural families) and assign less money to meat (1.2 percentage points for urban families and 4.4 percentage points for rural families). High-income rural families also decrease budget shares for fish, fruit, vegetables, drinks, and miscellaneous food items. On the other hand, high-income urban families decrease budget shares for fruit (0.4 percentage points) and drinks (0.3 percentage points).

In sum, our study suggests that either a 15 per cent decrease in income or a 20 per cent increase in rice prices leads, on average, to an increased share of spending on rice at the expense of decreased spending shares on other goods. An increase in rice prices decreases spending on meat, fish, and fruit and increases spending on miscellaneous food items (maize, bread, flour, milk, and others). In contrast, a decrease in income diminishes spending on miscellaneous food items. Finally, the effects of income and price shocks are heterogeneous across the income spectrum (low and high income) and location (urban and rural areas).

Our study estimated food demand in the Philippines and assessed how income and price shocks affect food purchasing behavior. Unlike most studies that evaluated food demand in a one-step budgeting process, we first examined the household's share of income spent on food. We then studied the allocation of food expenditures across the different food categories. Applying Lewbel's Stone- Lewbel (1989) method to address the absence of price data from the 2018 FIES, the evidence points to a relatively inelastic response of rice demand to prices and expenditures compared to that of other food groups. In addition, we found that income elasticity for rice was inelastic and that demand for rice was less elastic for higher-income urban households than for rural households. In the short term, a market shock such as a 15 per cent drop in income or a 20 per cent rise in rice prices leads families to spend more on rice, which is a less expensive main food staple, and to spend less on relatively more expensive food items such as meat, fish, and other food groups. The evidence points to a differentiated impact of income and rice price shocks on low-income and high-income households.

The findings from our study lead us to several policy recommendations. First, this research has shown that a decrease in income and an increase in rice prices can potentially worsen food insecurity in the most vulnerable and poorest segments of the Filipino population. This implies that the resilience of the poorest consumers and the most vulnerable households must be addressed by providing adequate safety nets. As Valera et al., (2020) pointed out, low-income families would be protected by those safety net measures when, and even before, the income shock threatens their food security. Safety net measures might include expanding existing cash transfer programs or developing new programs. Policymakers, however, would have to ensure that the safety nets are well targeted to the poor and have significant fiscal resources backed by the government.

Second, the Philippine Rice Industry Roadmap (PRIR) aims to fill a major gap in estimating the country's rice demand by different consumer types under a liberalized trading regime for 2021–2035. Thus, the elasticity estimates generated from our study would be helpful for simulation and further analysis of various programs under the PRIR, particularly programs that ensure access to nutritious food. If policymakers adopt this policy lesson, it will further allow them to quantify the welfare effects of the nutritional programs under the PRIR. This, in turn, will improve the quality of advice in the planning, designing, and implementing of government programs and policies.

Third, results from our study show that food demand behavior tends to be different for urban and rural households. Therefore, public policy should focus on designing and implementing a more targeted policy approach tailored to rural and urban areas. Policy efforts in this direction include programs that improve accessibility to and availability of quality agri-fishery products such as rice, fish, poultry, livestock products, fruits and vegetables, and other essential commodities at affordable prices in urban areas.

While highlighting the importance of public policy, our article still has many unanswered questions. Methodologically, demand estimation by different rice classes is essential but is missing. Considering this explicitly, the model can go beyond characterizing specific rice market segments to support modern breeding programs, product profiling, market intelligence, and research and policy implications. It is also essential to do a follow-up study when the next FIES becomes available. In this context, it would be good to know more about the income and price shocks imposed by the COVID-19 pandemic and how the pandemic affects the food purchasing behavior of different households.

An SSR of less than 100 per cent indicates inadequate food production. An SSR of 100 per cent suggests that the sector's food production capacity meets the population's needs. An SSR of greater than 100 per cent indicates that domestic production more than meets domestic requirements.

The Philippine Rice Industry Roadmap 2030 was created by the Department of Agriculture, Government of the Philippines. See, https://www.philrice.gov.ph/wp-content/uploads/2018/09/The-Philippine-Rice-Industry-Roadmap-2030.pdf .

Balié, Minot, and Valera (2021) show an analysis of the potential welfare effects of rice tariffication on different types of households, but they used only 2015 FIES data.

Food items included corns, rice, other cereals, fish, meats, fruits/vegetables, all others.

Note that the real per capita Gross National Product (GNP) declined by 20 per cent for four years in a row immedicately after the Philippines suspended payments on foreign debt.

Includes cabbage, water spinach, horseradish tree leaves, Chinese white cabbage, bitter gourd, eggplant, okra, tomato, hyacinth bean, mung beans, string beans, and others.

For studies discussing the advantages of rank three demand systems such as QUAIDS over other rank two demand systems, see, Decoster and Vermeulen (1998) and Cranfield et al., (2003) .

We conducted a quadratic specification test, which suggested favoring a QUAIDS model.

Additionally, the plot of food group shares over household expenditure and a formal test for quadratic specification in demand system analysis suggest the superiority of the QUAIDS model over AIDS in our estimation.

One can derive this by substituting ordinary intercept term |$\ {\alpha }_F$|⁠ , such that |${\alpha }_F = \alpha _F^{\prime} + \mathop \sum \limits_{d\epsilon D} {\delta }_d{Z}_d$|⁠ .

Most variation in SL prices is derived from household heterogeneity and not from CPIs.

The Lewbel (1989) definition of SL prices uses good-level price indices. The maximum level of disaggregation of CPIs in our data contains category-level price indices. Thus, we use category-level price indices rather than good-level price indices to compute the SL prices.

First-stage results can be obtained from the authors.

Note that the shares of budget allocated to food and non-food items add up to 1. The expenditure elasticity of non-food can be calculated as |${\varphi }_{NF} = \frac{{1 - {\varphi }_F*{S}_F}}{{1 - {S}_F}}$|⁠ .

https://psa.gov.ph/tags/family-income-and-expenditure-survey

The questionnaire consisted of seven parts: Part I ‒ Identification and Other Information; Part II ‒ Expenditures and Other Disbursements; Part III ‒ Housing Characteristics; Part IV—Income and Other Receipts; Part V ‒ Entrepreneurial Activities; Part VI ‒ Social Protection; and Part VII ‒ Evaluation of the Household Respondent by the Interviewer.

Derived by multiplying the expenditure elasticity by the sample mean income elasticity of food expenditures.

Quisumbing (1986) divided the sample into four quartiles.

We would like to thank all Funders who supported this research through their contributions to the CGIAR Trust Fund. In particular, funding from the CGIAR Initiative on Market Intelligence, the CGIAR Initiative on Foresight, and the Bill & Melinda Gates Foundation, Seattle, WA, USA [Grant no. OPP1194925] is greatly acknowledged. We also gratefully acknowledge the Philippine Statistics Authority for providing the 2018 Family Income and Expenditure Survey dataset. We further would like to thank the Editor and two anonymous reviewers for their constructive comments which greatly improved the paper.

The authors declare no conflict of interest.

Publicly available data can be obtained from https://psa.gov.ph/content/highlights-preliminary-results-2021-family-income-and-expenditure-survey-fies-visit-1 Price indices can be downloaded from https://psa.gov.ph/price-indices/cpi-ir/downloads .

Estimated Stone-Lewbel (SL) price indices, Philippines, 2018.

Notes: 1 Includes well-milled rice, regular rice, National Food Authority (NFA) rice, and other rice. 2 Includes maize and other cereals (maize, flour, cereal preparation, bread, pasta, and other bakery products). 3 Includes beef, chicken, goat, pork, and preserved. 4 Includes fish that is fresh, dried/smoked, preserved, and seafood. 5 Includes fruits that are fresh, dried, nuts, preserved, and others. 6 Includes vegetables, tubers, preserved, and products of tubers. 7 Includes centrifugal sugar, muscovado, refined brown sugar, and others. 8 Includes soft drinks, mineral, fruit juice, concentrates, and other non-alcoholic beverages. 9 Includes milk and others.

Numbers in parentheses are standard errors.

Socioeconomic attributes of families in 2018 FIES, Philippines.

Source: FIES 2018, Philippine Statistics Authority https://psa.gov.ph/tags/family-income-and-expenditure-survey .

Notes: Numbers in parentheses are standard errors. Region 1 = Ilocos; Region 2 = Cagayan; Region 3 = Central Luzon; Region 4 = CALABARZON and MIMAROPA Region; Region 5 = Bicol; Region 6 = Western Visayas; Region 7 = Central Visayas.

Notes: Numbers in parentheses are standard errors. Region 8 = Eastern Visayas; Region 9 = Western Mindanao; Region 10 = Northern Mindanao; Region 11 = Southern Mindanao; Region 12 = Southern Mindanao or SOCCSKSARGEN; Region 13 = National Capital Region (NCR); Region 14 = Cordillera Administrative Region (CAR); Region 15 = Autonomous Region in Muslim Mindanao (ARMM); Region 16 = Caraga; Region 17 = Bangsamoro Autonomous Region in Muslim Mindanao (BARMM).

Expenditure and price elasticities by income strata, urban subsample, Philippines, 2018.

Expenditure and price elasticities by income strata, rural subsample, Philippines, 2018.

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An Inter-Correlational Study on Socio-Demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines

The 1st International Conference on Business, Management and Information Systems 2019

Abstract ID: ICBMIS-2019-055

An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines

Marlon B. Raquel1, Anthony Greg F. Alonzo2

1 The Fisher Valley College, Taguig City, Metro Manila , Philippines 1 Graduate School, Taguig City University, Taguig City, Metro Manila , Philippines [email protected]

2 The Fisher Valley College, Taguig City, Metro Manila, Philippines 2 Department of Science and Technology, Taguig City, Metro Manila, Philippines [email protected]

The entry of new players in the fast food industry in the Philippines, both local and foreign companies, has paved for a more competitive business environment. Thus, the need to attend to the satisfaction of their customers has become their main objective. The main purpose of this study is to assess the relationships among socio-demographic characteristics, customer satisfaction, and customer loyalty in a fast food restaurant. Survey questionnaires were dis- tributed to respondents who dined in at the fast food store during the data gathering. Weighted means, standard deviations, verbal interpretations and rankings were determined to measure the level of customer satisfaction and customer loyalty. Spearman’s rho correlation coefficients were identified to assess the relationships. Respondents were satisfied in terms of food quality, service quality and price but were dissatisfied with the physical environment. Customer loyalty in terms of first-in-mind, word-of-mouth and repurchase intentions were high. Customer satisfaction indicators are significantly correlated with customer loyalty indi- cators at p-value .01. Food quality, service quality, physical environment, and price/perceived value for money are significantly correlated with repurchase intention, word-of-mouth, and first-in-mind – indicators of customer loyalty. Significant positive relationship between cus- tomer satisfaction and customer loyalty is established. Relationships between socio- demographic variables and customer satisfaction and loyalty vary. Fast food restaurants have to ensure that customers’ needs and expectations are met to increase their levels of satisfac- tion and customer loyalty. Recommendations, particularly on maintaining cleanliness of the physical environment inside and outside of the store at all times, and suggestions for future research are provided.

Keywords: Customer Satisfaction, Customer Loyalty, Fast Food Restaurant

1 Introduction

455 Marlon B. Raquel & Anthony Greg F. Alonzo The association between customer satisfaction and customer loyalty is one of the most im- portant relationships in business especially in the marketing field. Customer loyalty affects profitability of any business organizations. Businesses need to compete and cooperate in or- der to survive and maximize its profits. A big deal in realizing this two-fold goal is to satisfy their customers and retain them as loyal customers in the long run. The relationship between satisfaction and loyalty of customers is associated with customers’ attitudes toward products and/or services and buying patterns of customers. The levels of satisfaction and loyalty may also vary based on the socio-demographic characteristics of customers. Studying the relation- ships among these three variables provides understanding on consumer behavior.

Looking upon different organizations, their priority seems to focus on how they can keep their customers. Customers are longing for many things that would address their needs – food being one of the basic necessities. Using Abraham Maslow’s Hierarchy of Needs, Hatch (2014) of Feedback Systems Company which focuses on market research, concluded that customers, who are more satisfied, stay longer, recommend more, and buy more compared to their less satisfied counterparts. In an article published by Keiningham, Gupta, Aksoy and Buoye (2014) in Massachusets Institute of Technology Sloan Management Review entitled “The High price of Customer Satisfaction”, the authors stated that “managers often assume that improving customer satisfaction and financial performance go hand in hand. The reality, however, is more complex.” This means there is no clear relationship between satisfaction and customer’s buying behavior in the future. This finding echoes one key result of the study of Danny Rueda Cruz of the University of the Philippines published in The Philippine Star (October 9, 2001). The researcher found that customers, while they were satisfied of the food, were not loyal to any particular fast food store. Nevertheless, customer satisfaction plays a vital role in making businesses sustain their growth as evidenced by numerous customer satisfaction surveys being conducted by compa- nies. This is true to all kinds of industries specifically the food service industry. Business owners of food service stores must understand that customers who are dissatisfied with their products and services drive them away. When customers are not satisfied with the products or services the company provides, there is a higher chance that these unhappy customers will not patronize the company anymore. Worse than that is they may spread the bad news instead of the good news. When this happens, it creates poor customer service which translates to lower sales, thus, lower profits. Therefore, organizations are required to change or modify their existing marketing strategies and business policies in order to meet fast-changing cus- tomer preferences. When these preferences are met, customer satisfaction follows. According to the report published by Our Life Policy Research (2015), the global fast food market grew by 4.8% in 2006. Yates (2012) of the Motley Fool, which owns shares of McDonald’s and PepsiCo, states that in 2014, the global fast food market share could reach $239.7 billion which is an increase of 19.5% since 2009. The world’s population is at seven billion and is expected to exceed 9 billion in 2050 (United Nations, 2009). This means more people, more customers. As population becomes bigger, marketers expect that fast food consumption becomes higher which means more prof- its for fast food chains owners. In the Philippines, fast food business is a lucrative market. In a country report of Eu- romonitor International (2014), fast food market is the largest and the fastest-growing catego- ry in the foodservice industry. In 2012, the total foodservice revenue amounted to Php121.9 billion which is equivalent to 30% of the total value sales in consumer foodservice. Based on the same report, the fast food market is expected to be the biggest category in the foodservice industry in the Philippines by the end of 2017.

456 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines In a report published by the National Statistics Office in 2012, the country had a total of 13,119 establishments engaged in food and beverage services. Of this number, fast food chains ranked second with 2,535 establishments. With all these statistics, fast food service industry is now a global phenomenon with customers actively finding companies that would meet their expectations on products and services. The emergence of new players on the fast food market makes competition fiercer than before. The entry and subsequent expansion of branches of foreign fast food chain com- panies in the Philippines is a clear indication on this issue. With increasing competition among these fast food stores, both attracting new customers and retaining them become focal points of marketing strategies of companies. Enlarging the customer base creates revenues and retaining them gives more opportunities to earn more profits. It is imperative that fast food companies know customers’ needs and what satisfies them. Knowing the preferences of the customers may start by getting information on their so- cio-demographic characteristics. Preferences vary from one customer to the other. A competi- tive market provides many options for the customers to choose from. Understanding custom- er satisfaction would give business owners ideas on how to keep their customers loyal to their companies, thus, conducting a study on the relationship between satisfaction and loyalty is important. Business organizations have given much attention to the concept of customer satisfac- tion because of its relationship to business profitability. It is therefore natural for the owners and managers to conduct customer satisfaction studies for their own organizations. In the case of fast food chains like the leading fast food corporation in the Philippines, which is the focus of this study, the same marketing principle holds true. Fast food is a term used for food which are prepared and served quickly. There is a minimum time required to prepare the food. According to Kandampully and Suhartanto (2000), customer satisfaction is the most important consideration for any business. Without satisfied and happy customers, organiza- tional survival will not be guaranteed. In order to make the customers happy, the researchers suggested that it is important for the organizations to modify their business strategies. When doing so, an important consideration on customer satisfaction must be taken into account since customer satisfaction results in loyalty to the company which will create an impact on the overall business profitability. Burke Incorporated, in its white paper entitled Advances in Customer Loyalty Meas- urement published in 2000, states that loyalty can be measured in terms of the likelihood of future purchases of customers and the likelihood to recommend the company to others. When people are satisfied with the products, the normal tendency is to visit the store and buy the products again. In addition, customers would spread the good news to other people as well. While many literatures established a clearly positive relationship between customer sat- isfaction and customer loyalty, there are studies that failed to generalize this finding. Cus- tomer satisfaction does not always mean customer loyalty. There are customers who are satis- fied with the products and/or services of a company but shift patronage to other companies offering the same line of products and/or services and some unsatisfied customers remain loyal (Ganesh, Arnold & Reynolds, 2000). In other words, the positive relationship between customer satisfaction and customer loyalty does not apply to all situations (Kamakua, et al, 2002). Several questions need to be addressed by the researcher. First, is it true to customers of the leading fast food store that when they are satisfied, they are more likely to be loyal to the company? Second, will the findings of previous researches, i.e., customer satisfaction translate to customer loyalty, be applicable to fast food store under study? The store under study is the largest fast food chain in the Philippines. It is 100% Filipi- no-owned company. According to its website, it “enjoys the lion share of the local market

457 Marlon B. Raquel & Anthony Greg F. Alonzo that is more than all other multinational brands combined.” In addition, 96 of its 2,510 stores are located outside the country which means that it is gaining ground in the international market. Rappler.com (2014) reports that it ranks among 10 best foreign fast food chains in the United States citing a survey conducted by The Daily Meal, a US-based website. In terms of gross revenues, the company ranked first among fast food chains in the country which reached almost P70 billion in 2009 (Business World’s Top 1000 Corporations, 2011). While it is the most popular fast food in the Philippines, it has to compete with its competitors in order to sustain its growth. Customers have many choices because there are many fast food chains which offer similar food items. The growth on the number of outlets, sales transactions and revenues remains vibrant. With the increasing number of malls and supermarkets being built across the country, busi- nesses are assured of healthy competition. It is imperative that understanding the relationship between customer satisfaction and customer loyalty in fast food industry is essential in order for the organizations associated with fast food industry to develop sound marketing strategies. Increasing the level of satisfac- tion of customers may help fast food industry organizations retain their customers, i.e., en- hancing customer loyalty, which would eventually lead to higher business profitability.

2 Literature review

2.1 Customer Satisfaction in Fast Food Industry

The topic of consumer satisfaction is widely discussed among many writers. There have been countless articles about this topic. In fact, if one types the phrase ‘consumer satisfaction’ on Google search, there are around 8.5 million websites that mention it. If the phrase ‘cus- tomer satisfaction in fast food’ is typed, around 5 million websites are being crawled by Google. This attests the importance of customer satisfaction worldwide. Ross Beard, a contributor of Client Heartbeat Blog, helps businesses improve customer satisfaction, customer retention, and customer loyalty by publishing articles on these topics. In one of his articles dated January 20, 2014, he mentioned about why customer satisfaction is important. According to the author, customer satisfaction is a leading indicator of consum- er repurchase intentions and loyalty. He recommended that businesses should emphasize ex- ceeding customer expectations. The American Customer Satisfaction Index is the ‘only national cross-industry measure of customer satisfaction in the United States’ based on the organization’s website (2015). Annually, it captures customer opinions about critical elements of the customers’ dining ex- periences such as staff courtesy, service speed, food services, store layout and cleanliness, and variety and quality of food and beverages by conducting series of surveys across the United States. These attributes are widely studied in the fast food industry. The concept of customer satisfaction becomes a driving force for Philippine businesses to create marketing strategies that would satisfy their customers. The leading fast food chain, for instance, states in its website that customer satisfaction has always been the key to the corporation’s success. It is now the market leader among fast food chains in the country. Its market share is more than half of the entire fast food service industry. According to Euromonitor International’s article published in its website on November 2013, fast food is still the largest and the fastest-growing category in the Philippine consumer foodservice industry which accounts for 30% of total value sales in consumer foodservice. The book of Dionisio Magpantay and Don Magpantay entitled Principles of Marketing Philippine Setting published in 2012 extensively discussed personal factors that affect con- sumer behavior. For example, the authors stated that companies and businesses need to know

458 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines what influences their customers in purchasing products or services. Satisfying the needs and wants of the customers makes man justifies his existence. These personal factors, such as family-oriented approach, are claimed as the heart of the leading fast food chain’s success. The Personnel Management Association of the Philip- pines (PMAP), the largest group of human resource practitioners in the country, awarded it an Employer of the Year Award. Hewitt Associated gave Best Employer in the Philippines Award to the company as well, and the company also receives a citation as a Top 20 Employ- er in Asia from the Asian Wall Street Journal. These awards, among others, are manifesta- tions of continuous and consistent quality products and services it provides to its customers (2015). In the recent article published in Rappler on October 1, 2014, it states that a US-based food website, The Daily Meal, ranked the fast food chain as one of the top 10 fast food stores in the United States. “Fast food may seem like a strictly American tradition, but just about every country has fast food and fast casual chains of its own nowadays. For better or for worse, some of these chains have come to the United States … we welcome [them] with open arms,” The Daily Meal wrote. The concept of customer satisfaction is one of the most popular topics in marketing be- cause it affects business profitability whether in positive or negative manner (Gonzalez, Comesana, & Brea, 2007). All business organizations are concerned with how they will at- tract new customers and retain them. Customer satisfaction, in fact, is one of the most im- portant considerations in the field of fast food service industry. Anderson and Mittal (2000) found that satisfied customers are more likely to contribute business profitability. Numerous studies suggest (e.g., Nezakari, Kuan & Asgari, 2011) rivalry in the fast food industry is getting more intense with the increasing number of fast food outlets and other food industries such as traditional restaurants which offer a fresh, variety of tasty foods and full services. To compete in the industry, local fast food restaurants must keep track of their customers, improve and change according to their customers’ need and also mentioned that to be able to judge customers’ satisfaction levels and to apply that knowledge potentially it must give a hospitality advantage over competitors via such benefits as product differentiation, in- crease customer retention, and positive word-of-mouth communication. No business, fast food chain in particular, will exist without customers. In the study of Victoria and Paragua (2012), it was found that all dimensions of service quality are important in maintaining satisfaction among customers in one of the largest fast food stores in the Phil- ippines. The authors concluded that the fast food outlet adhered to the FSC (Food-Service- Cleanliness) Standards of the parent company which contributed to its success. Chen, Chen, and Liu (2009) analyzed fast food buying behaviour in Metro Manila in the study entitled Expansion Trend of Fast Food Franchises in Metro Manila and utilized the four Ps of marketing in determining what affects buying behavior toward fast foods. The re- search, which covered 12 different fast food store outlets, revealed that the success of Ma- nila’s fast food industry can be attributed to its standard processes, enhancement of values, quick services provided, and distribution right. The study further showed that the most im- portant features of the fast food restaurants are cleanliness, price, staff etiquette, dining envi- ronment, food quality, and consistency.

2.2 Customer Loyalty in Fast Food Industry

In the article published by Bill Nissim entitled Brand Loyalty: The Psychology of Pref- erence (2006), he mentioned about Martin Lindstrom’s Brand Sense concept. According to this concept, the ultimate goal of a business is to have strong, positive, loyal bond between

459 Marlon B. Raquel & Anthony Greg F. Alonzo brand and consumer so the consumer will turn to brand repeatedly. This return patronage is what the researchers termed as customer loyalty. A magazine article published in QSR on its February 2012 issue explained that in order for the fast food stores to create repeat business, they need to set realistic goals. One major challenge fast food is facing is that customers do not stick to just one store when dining alt- hough they keep on coming on the same store. This observation was also noted in a market survey conducted by TNS Intersearch (2003), a market research firm in the United States. Fast food restaurants have weaker base of loyal customers than other national chains that spend less on marketing activities. The article (QSR Magazine) further suggested that gimmicks such as loyalty programs and event-specific promotions can be done to attract customers. The article further stated that getting an average visit of 3 to 5 times a month for a customer who usually visits 10 times in a restaurant is an indicator that the store is likely the preferred fast food. Neil Kokemuller of Demand Media and also a marketing professor from Iowa State University wrote an article in Houston Chronicle entitled Customer Loyalty in the Fast Food Industry (2012). In this article, he stated that there are specific criteria that contribute to cus- tomer loyalty and they vary from one customer to another. These criteria are efficiency, cus- tomer service, product quality, pricing and family-friendly atmosphere of the fast food stores. One example of building customer loyalty is the strategy that Del Taco implemented which makes it the second largest Mexican fast food chain in the United States (Bloomberg Business Week, 2008). According to the company’s president, Shirlene Lopez, Del Taco chain’s success can be attributed to respect that customers deserve. Employees should treat customers with respect and the same respect must be given to the employees by the manage- ment. She further stated that looking at the eyes of the customers when talking to them is one way of showing respect. An article published in The Philippines Star (2001) comprehensively discussed about a book entitled Fast Food Nation: The Dark Side of the All-American Meal. The author, Eric Schlosser, spent two years of conducting researches and eating an enormous amount of fast food. He said that most of it tasted pretty good. He further said that taste is ‘one of the main reasons people buy fast food; it has been carefully designed to taste good.’ This particular observation was compared by the author of The Philippine Star column with the findings of a study conducted by Danny Rueda Cruz of the University of the Philip- pines. Cruz conducted a survey of 400 customers of fast food restaurants and how Filipinos define quality and what makes the customers loyal. Based on the report, Filipinos ranked fla- vour and taste as the top criteria why they keep on returning the same fast food stores. How- ever, he emphasized that there seems to be no loyalty among Filipino fast food customers be- cause they ‘jump from one fast food to another’ easily. Nevertheless, fast food chains continue to provide loyalty cards to their customers (Reyes, 2011). According to the report, several loyalty cards have unique promotional strate- gies. For example, Shakey's has Pizzanatic Supercard, Pizza Hut has Palm card, Angel Pizza has Privilege card, and McDonald's has Midnight card. Some companies offer ‘buy one, take one’ promo. In the case of Jolibee, the company’s Happy Plus Card offers points for every purchase. Every P50 entitles the customer to earn 1 point which is equivalent to one peso. Companies have forged partnerships with other companies to create customer loyalty programs. For instance, Jolibee Foods Corporation and Bank of the Philippine Islands joined forces in introducing the Happy Plus Card, the first of its kind system in the fast food indus- try (Kabayan Tech, 2012). This loyalty card for Jolibee customers can earn points for every purchase. Every Php50 transaction is equivalent to one point which is equal to one peso. BPI provides the payment infrastructure.

460 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines According to Gee et al. (2008), the advantages of the customer loyalty are; (1) cost less to serve the customers; (2) customers will pay a higher cost for a set of products; and (3) customers will act as product or service ambassadors via word of mouth for the compa- ny. Therefore, it is important to study the factors that affect customer loyalty and results in desired buying behaviour (Lee & Lambert, 2000). Wang and Zhao (2007) noted that fast food companies are required to influence the customer loyalty and adopt those strategies which could be helpful in building the loyalty of the customers. Researchers such as Lee, Hsiao and Yang (2010) found that one of the factors that fast food companies can enhance their loyalty program is by improving the service quality be- cause high service quality can contribute to satisfying the customers. In fact, fast food com- panies are investing money on training and development of their employees so that they can effectively provide quality customer service which in turn enhance satisfaction of customers (Sudhahar, Israel & Selvam, 2006). Competition among restaurant industry, particularly the fast food sub-sector, is fierce nowadays. There is a vast opportunities for market but consumers are price conscious and exhibit brand loyalty (Edralin & Castillo, 2001). Therefore, business managers must make sure that their customers are satisfied with their product and service offerings. While the study of Enriquez-Magkasi and Caballero (2014) focused on customer satis- faction and loyalty in Philippine resorts, it has explored dimensions of service quality that af- fect loyalty to the company which are similar to the fast food industry. Flores (2013) recommended that to attract more regular customers, fast food chain stores can serve same kind of products but can be distinguished from one another. Moreover, the author suggested that more advertisements should be put through different media of communications.

2.3 Measures of Socio-demographic Characteristics

Several studies pointed out the relationship between socio-demographic variables of re- spondents and customer satisfaction. For example, in the study of Abdullah and Hamdan (2012), results showed that age and monthly income have a significant relationship with all dimensions of customer satisfaction. Educational attainment was related to technological and sales and marketing aspects. While gender was found a significant relationship with customer satisfaction in the study of Abdullah and Hamdan (2012), the study of Raza et al (2012) found no significant relationship between the two variables. Female customers exhibit higher levels of loyalty (Mittal & Kamakura, 2001; Petter- son, 2007; Verboef & Donkers 2005). Since female customers generally place a higher value on long-term relationships, they also tend to be more loyal than males (Petterson, 2007). Household income is believed to positively influence the level of customer loyalty (Keaveney & Parthasarathy, 2001; Verboef & Donkers, 2005). Customers that are more con- cerned with prices tend to be less loyal because lower household incomes lead to increased price comparisons, thus, lowers loyal. Similarly, higher income customers tend to be more loyal (Shankar et al, 2003). Existing research (Mittal & Kamakura, 2001) has also been consistent with the fact that higher levels of education are associated with lower levels of loyalty. As education levels in- creases, so does the customers’ need for information related to their purchase intention, thereby increasing purchasing involvement. This association between educational levels and purchasing involvement suggests that educational levels should be negatively associated with loyalty.

461 Marlon B. Raquel & Anthony Greg F. Alonzo 2.4 Measures of Customer Satisfaction

2.4.1 Food Quality

Food quality is one of the most important components of any dining experience (Namkung & Jang, 2007; Sulek & Hensley, 2004). This finding was validated by the study of Clark and Wood (1999) which found that food quality is a primary factor influencing cus- tomer satisfaction and loyalty. Mattila (2001) identified top three reasons why customers pat- ronize their target restaurants: food quality, service quality, and atmosphere. Moreover, Fu and Parks (2001) examined the quality of food item as one of the 24 items used in the survey questionnaire to measure diners’ perceived quality of restaurant service. Several researches used different sets of constructs to measure food quality. Risjswijk and Frewer (2008) measured the variable in terms of taste, good product, natural/organic and freshness. Other measures include presentation, health options, taste, freshness, and tempera- ture (Namkung & Jang, 2008) and freshness, presentation, taste, and innovative food (Sha- harudin et al, 2011). Shaharudin, Mansor and Elias (2011) concluded that freshness of the food is the most important food attribute among Malaysian customers, followed by presenta- tion and taste.

2.4.2 Service Quality

The causal relationship between service quality and customer satisfaction has been a major focus on several studies in the fast food industry and findings are not always con- sistent. Relationships among service quality, consumer satisfaction, and purchase intentions were examined. The researchers found that service quality was an antecedent of consumer satisfaction while consumer satisfaction was not a significant predictor to service quality. The most common method of measuring service quality is the SERVPERF Model pro- posed by Parasuman, Zeithaml, and Berry (1985). This model consisted of five dimensions, namely, tangibility which includes the physical environment and the equipment used to pro- vide their products and services; reliability which includes company’s regularity and con- sistency in providing services to clients; responsiveness which refers to the willingness of staff to provide quick service and prompt response to customers; assurance which means the knowledge and courtesy of employees and their ability to convey trust to customers; and em- pathy which means caring, individualized attention given to costumers.

2.4.3 Physical Environment

There are previous studies on food service industry that focused on the atmospheric as- pect or the physical settings of the store. Ryu and Han (2010) examined how perceptions of customers of physical environment influence customer satisfaction and customer loyalty. Fa- cility aesthetics, lighting, layout and social factors have significant effects on disconfirmation which in turn had direct influences to customer satisfaction and loyalty. The study of Ryu and Han (2010) showed that if the condition of the fast food environment is improved, more customers would be satisfied. Physical environments, such as spatial layout of a service organization which includes the arrangement of furniture and equipment, may also influence consumer buying behavior. According to Wall and Berry (2007), this physical environment may affect customers’ physi- cal comfort and movement. Other researchers examined variables such as physical environment of the restaurant (Meng et al, 2008; Kim, 2008), decor and design (Han et al., 2009; Namkung et al, 2008),

462 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines cleanliness, atmosphere, and space (Han et al., 2010; Andaleeb et al, 2007; Yukse et al, 2003).

2.4.4 Price/Perceived Value for Money

Price or the perceived value for money has a significant role in selecting a product. Price is one of the four P’s of Marketing Mix that has significant role in implementation of marketing strategy (Kotler & Armstrong, 2012). Han (2009) claim that one of the most adaptable factors which improved quickly is the pricing (Andalleb et al., 2006). Andaleeb and Conway (2006) found that service quality, price expectation, and food quality influenced cus- tomer satisfaction in that order of degree of importance. In the study of Voon (2011) among Malaysian customers, it was found that price is one of the key determinants on satisfaction and loyalty, the other factor was human service. This finding was validated a year later with the study of Sahari, Basir, and Jangga (2012) where researchers concluded that food pricing influenced customer satisfaction among customers in Malaysia. Quin and Prybutok (2008) investigated the role of price/value for money in determining customer satisfaction in fast food restaurants. While the findings suggested that the role of price did not find it to be significant because of the relatively low prices of products, the young consumers who are not economically strong may have find price as a motivating factor why they have dined at the restaurants.

2.5 Measures of Customer Loyalty

2.5.1 Repurchase Intention Word-of-Mouth and First-in-Mind

There are several studies that measure customer loyalty in terms of repurchase intention (Taleghani, Largani, & Mousavian, 2011; Fullerton, 2005; and Johnson et al, 2006). Repur- chase intentions simply refer to the likelihood of using a brand again in the future. Yi and Suna (2004) measured repurchase intention with two indicators: repeat purchase intention and repurchase probability. Taleghani, Largani, and Mousavian (2011) adapted re- purchase intention in their study with five items. Hayes (2009) concluded that customer loyalty is directly related to financial growth of the company. The researcher used number of referrals which is word of mouth, purchase again, purchase different products, increase purchase size and customer retention or defection size as measures of customer loyalty. Boonlertvanich (2011) used variables repurchase intention, word-of-mouth, and first- in-mind to measure customer loyalty in Thailand’s banking sector. As a result, customer per- ceived value has a great impact on customer loyalty.

Figure 1 Conceptual Framework of the Study

SOCIO-DEMOGRAPHIC PROFILE Age Gender Income Education CUSTOMER LOYALTY First-in-Mind Word-of-Mouth CUSTOMER SATISFACTION Repurchase Intention Product Quality Service Quality Physical Environment 463 Price/Perceived Value for Money

Marlon B. Raquel & Anthony Greg F. Alonzo

Figure 1 shows the conceptual framework of this study. This framework is own con- struct based on the existing studies on customer satisfaction and loyalty in the fast food ser- vice industry. Relationships on three variables – socio-demographic characteristics of the re- spondents, customer satisfaction, and customer loyalty were tested. Socio-demographic characteristics include age, gender, education, and income. There are numerous studies that used item indicators for food quality (Shaharudin et al, 2011; Namkung & Jang, 2008; Rijswijk & Frewer, 2008; Sulek & Hensley, 2004; Soriano, 2002; Susskind & Chan, 2000). Example of research that has previously explored service quality and physical environment indicators is the research of Bernarto, Meilani and Kusuma (2013). As for the price/perceived value for money, the SERV-PERVAL Scale (Petrick, 2002) was used. Measurement indicators of customer loyalty was used based on the previous studies (Enriquez-Magkasi & Caballero, 2014; Mojares, 2014; Petrick, 2002).

3 Methodology/Materials

3.1 Research Design

The researcher used the descriptive-correlation design in this study due to its appropri- ateness to the problem. Correlations among socio-demographic profile, customer satisfaction, and customer loyalty were identified. It involves collection and analysis of data to be gath- ered in order to identify the rate of customer satisfaction in the leading fast food store in Taguig City. This section focuses only on individual-level of satisfaction assessment. It is in- tended to serve as a resource for those who wish to assess their satisfaction in a research study. Data and market analysis cultivates the organization’s awareness of the fast food mar- ket and the greater competitive environment, ensuring accurate and focused strategies of the business. The study utilized the survey method. The researcher produced questions for food qual- ity, service quality, physical environment, and price/perceived value for money.

3.2 Sampling Techniques and Respondents of the Study

Convenience sampling was used to attain the number of respondents on the selected fast food chain. An adequate sample size is necessary to determine statistical power of the findings. Since the population of customers in a fast food chain cannot be determined, it would be impossible to use any formula, e.g., Slovin’s formula. The proponent distributed 420 questionnaires. Of this number, 400 were completed questionnaires. The 20 question- naires were considered spoiled due to too many items that were left unanswered. Therefore, the response rate is 95.24%. The respondents of this study were customers of the leading fast food store in Taguig City. This company was chosen due to its reputation of customer satisfaction and its success in its business operations. To describe the characteristics of the respondents, age, sex, educa- tional attainment, and monthly income were asked.

3.3 Research Instrument

The research instrument used was a survey questionnaire which makes any data gather- ing fast and gets accurate information. The researcher provided questions about food quality, service quality, physical environment, and price/perceived value for money. Measures for overall customer satisfaction and customer loyalty were included in the questionnaire as well.

464 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines The survey questionnaire is divided into three parts. First, respondents were asked about their socio-demographic characteristics, i.e., age, gender, monthly income, and highest educational attainment. Age and income were treated as continuous variables measured in years and in pesos, respectively. Gender was considered nominal variable while educational attainment was considered as ordinal data. The second part deals with measures of customer satisfaction and customer loyalty. A research instrument must operationalize the research questions and the conceptual frame- work. Five categories under satisfaction were measured with each category having five items. Likewise, to measure the level of customer loyalty, five measurement items were treat- ed. Responses were in the form of 4-point Likert scale. The rating of ‘1’ signify that the cus- tomer ‘strongly disagree’ with the statement, ‘2’ for disagree, ‘3’ for agree, and ‘4’ for ‘strongly agree.’ To measure the internal consistency of constructs used in the study, Cronbach’s alpha was used as shown in Table 1. The minimum level of generally accepted Cronbach’s alpha value is 0.70 (Taber, 2016; Cortina, 1993). The higher the value is, the more reliable and con- sistent the items are on each scale.

Table 1 Cronbach’s Alpha Reliability Statistics Marketing Mix Elements Cronbach’s Alpha Number of Items Food Quality .791 5 Service Quality .822 5 Physical Environment .738 5 Price/Perceived Value for Money .827 5 Repurchase Intention .820 5 First in Mind .859 5 Word of Mouth .872 5

3.4 Statistical Treatment of Data

Three kinds of statistical analyses will be conducted in this study. The following dis- cussion presents three sections. The first section describes univariate analysis. Frequency and percentage distributions, weighted means, composite mean scores, and standard deviations are discussed. The second section deals with bivariate analysis which includes cross tabula- tions and chi-square tests. The third section presents correlational analyses among different variables to test the association among them. Spearman’s rho was used to test correlations among variables. Spearman Rank Correlation Coefficient uses ranks to calculate correlation. This study used ordinal data, Likert items which were ranked, thus Spearman’s rho is the most appropriate correlation statistics to use. Interpretation of numerical values is given be- low: r > 0 implies positive agreement r < 0 implies negative agreement r = 0 implies no agreement

3.4.1 Univariate Analysis

Frequency and percentage distributions of respondents in each of the characteristics un- der consideration will be employed. This is the simplest form of univariate analysis. It de-

465 Marlon B. Raquel & Anthony Greg F. Alonzo scribes the characteristics of respondents in terms of socio-demographic variables, i, e., age, sex, income, and educational attainment. The formula for percentage distribution is as follows:

%=F/n x 100

Where: %= Percentage F= Frequency n= Total number of respondents

To describe the level of customer satisfaction and extent of loyalty of each variable, weighted means were explored. The constructs investigated in this study were measured us- ing a 4-point Likert scale anchored by 4 as ‘very satisfied’ and 1 as ‘not satisfied.’ In addi- tion, composite mean scores for all dimensions were determined through two steps. First, mean scores of the respondents’ answers in each item of every dimension were computed. Second, the mean of these mean scores was calculated by adding all mean scores then divide the sum by five which is the number of items per dimension. Moreover, the total weighted mean for customer satisfaction was calculated by adding the four mean scores then divide the sum by four dimensions. Higher mean scores signify higher degrees of satisfaction and loyal- ty.

3.4.2 Bivariate Analysis

The second part of data analysis is bivariate analysis which describes levels of satisfac- tion and loyalty in relation to the four socio-demographic variables. Frequency and percent- age distributions of respondents will be presented by cross-tabulating the profile characteris- tics by four satisfaction indicators and three loyalty indicators. Cross tabulations and chi-square analysis allow statistical tests of significance whether a systematic relationship exists of the joint frequency of two or more variables in the study. The likelihood ratio chi-square statistics is the most fundamental measure of overall fit. The larger the chi-square value, the better. To test the relationships among variables under study, correlation coefficients were de- termined. In measuring the relationship between customer satisfaction and customer loyalty, Spearman’s rho ( ) correlation was used.

4 Results/Findings

4.1 Profile of the Respondents

Table 2 shows the profile of the respondents by selected socio-demographic character- istics. About 21.2% of the respondents are 17 years old and below while those who are 40 years old and above comprise 14.4% of the total number of respondents. Majority of the re- spondents belong to age group 18-39 equivalent to 64.4% of the total number of respondents. More than half of the respondents are single (51.2%), followed by those who are al- ready married (47.5%), and widowed (1.2%). About 30% of the respondents have monthly income below P5,000, followed by income higher than P20,000 (23.8%), P5,000 to P10,000 (18.1%), P10,001 to P15,000 (15.0%), and P15,001 to P20,000 (13.1%).

466 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines Profile of the Respondents Socio-demographic Characteristics Frequency Percentage Age 10-19 164 41.0 20-29 159 39.8 30-39 50 12.5 40-69 27 6.7 Gender Male 148 37.0 Female 152 63.0 Highest Educational Attainment 3 0.7 Elementary 118 29.5 High School 258 64.5 College 14 3.5 Master’s 7 1.8 Doctorate Income P10,000 and below 155 38.8 P10,001-P20,000 161 40.2 P20,000-P30,000 58 14.5 P30,001 and above 26 6.5

4.3 Customers’ Levels of Satisfaction

Table 3 Customers’ Level of Satisfaction in Fast Food Restaurant in terms of Food Quality

Food Quality Weighted Standard Verbal Rank Mean Deviation Interpretation 1. Different menu are available. 3.24 .650 Strongly Agree 3 2. The food has a pleasing appearance. 3.22 .689 Agree 4.5 3. The food is clean. 3.32 .655 Strongly Agree 2 4. The food has a good taste. 3.42 .659 Strongly Agree 1 5. The quality of food is excellent. 3.22 .667 Agree 4.5 Composite Mean 3.28 Strongly Agree

Table 3 presents customers’ level of satisfaction in fast food store in terms of food qual- ity. Results showed that the respondents strongly agreed that the food has a good taste with a weighted mean of 3.42. It ranks first among the five food quality items. This is followed by the cleanliness of food with a weighted mean of 3.32 and the availability of different menu with a weighted mean of 3.24. Customers put premium on food taste, cleanliness of food, and availability of different menu as shown by the degrees of agreement which are all ‘strongly agree’. The pleasing appearance of food and its quality both have weighted means of 3.22 with verbal interpretation of agree. The composite mean for food quality is 3.28 with a verbal interpretation of ‘strongly agree’. Food quality remains the top priority of customers when looking for food to eat at fast food chains. This finding is consistent with previous researches (Namkung and Jang, 2007; Sulek and Hensley, 2004, Matilla, 2001). For instance, Matilla (2001) indicated that among the top three reasons why customers patronize their restaurants, food quality comes first. Specifically, food quality was the most important attribute that affects both customer satisfac- tion and customer loyalty.

467 Marlon B. Raquel & Anthony Greg F. Alonzo Customers’ Level of Satisfaction in terms of Service Quality

Service Quality Weighted Standard Verbal Rank Mean Deviation Interpretation 1. The employees are courteous. 3.05 .610 Agree 3 2. The employees provide service quick- 2.57 .715 Agree 5 ly and accurately. 3. The employees are knowledgeable and 3.10 .601 Agree 1 skillful. 4. The employees are willing and able to 2.81 .682 Agree 4 provide service in a timely manner. 5. Employees are patient when taking or- 3.08 .703 Agree 2 der. Composite Mean 2.92 Agree

Generally, customers agreed that employees of the fast food store are knowledgeable and skillful (WM=3.10), patient when taking their orders (WM=3.08), courteous (WM=3.05), willing and able to provide service in a timely manner (WM=2.81), and provide service quickly and accurately (WM=2.57), in that order, as shown in Table 4. The composite mean for service quality is 2.92 with a verbal interpretation of ‘agree’.

Table 5 Customers’ Level of Satisfaction in terms of Physical Environment

Physical Environment Weighted Standard Verbal Rank Mean Deviation Interpretation 1. The store has spacious seating arrange- 2.52 .743 Agree 3 ments. 2. Surroundings are neat and clean. 2.24 .841 Disagree 5 3. The store has attractive building and 2.31 .722 Disagree 4 dining area. 4. The store has sufficient lighting. 2.56 .668 Agree 2 5. The store has modern looking equip- 2.72 .785 Agree 1 ment. Composite Mean 2.47 Disagree

Respondents agree that the store has modern looking equipment as shown in the weighted mean of their responses which is 2.72, the highest among five items of physical en- vironment indicators. This is followed by the observation that the store has sufficient lighting with a weighted mean of 2.56 and it has spacious seating arrangements with a weighted mean of 2.52. When respondents answered on the statement ‘The store has attractive building and dining area’, they disagreed on it with a weighted mean of 2.31. When it comes to the neat- ness and cleanliness of the store’s surroundings, respondents also disagreed as evidenced by the weighted mean of 2.24, the lowest mean score of all five indicators. The resulting compo- site mean is 2.47 with verbal interpretation of ‘disagree’ as shown in Table 5.

Table 6 Customers’ Level of Satisfaction in terms of Price/Perceived Value of Money

Price/Perceived Value for Money Weighted Standard Verbal Rank Mean Deviation Interpretation 1. The products offered in this store are 3.11 .664 Agree 3

468 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines reasonably priced. 2. This fast food store offers value for 3.12 .607 Agree 2 money. 3. The store offers good products for the 3.20 .669 Agree 1 price. 4. Purchasing products in this store 3.09 .690 Agree 4 would be economical. 5. Price discounts and/or earning points 3.20 .728 Agree 1 through loyalty program are very good strategies. Composite Mean 3.14 Agree

Table 6 presents customers’ level of satisfaction in the fast food store in terms of price/perceived value for money. All price indicators have weighted means with correspond- ing verbal interpretation of ‘agree’ which translates to the fact that customers are generally satisfied. The composite mean is 3.14. As to rankings, respondents believed that the store of- fers good products for the price (Rank 1; WM=3.20) and price discounts and earning points through loyalty program are very good strategies (Rank 1; WM=3.20). Respondents also be- lieved that the leading fast food store offers value for money (Rank 2; WM=3.12), followed by the statement that the products offered in the store are reasonably priced (Rank 3; WM=3.11). Meanwhile, the belief that purchasing products in the store would be economical ranked last with a weighted mean of 3.09.

Table 7 Composite Mean Scores of Customer Satisfaction Indicators

Customer Satisfaction Weighted Verbal Rank Mean Interpretation Food Quality 3.28 Agree 1 Service Quality 2.92 Agree 3 Physical Environment 2.47 Disagree 4 Price/Perceived Value for Money 3.14 Agree 2 Composite Mean 3.00 Agree

Table 7 summarizes the weighted means and the composite mean of customer satisfac- tion indicators. Among the four indicators, customers placed food quality as the primary indi- cator of satisfaction with a weighted mean of 3.28. Next is price/perceived value for money with a weighted mean of 3.14. This is followed by service quality with a weighted mean of 2.92. Last in rank is the physical environment indicator with a weighted mean of 2.47. Among the five indicators, physical environment of the store received the least degree of agreement of customers. With a weighted mean of 2.47, respondents are dissatisfied with the physical environment of the store which includes neatness and cleanliness of the store and the attractiveness of its building and dining areas. Overall, respondents are generally satisfied with a weighted mean of 3.00. The findings are consistent with previous studies that the top reasons for patronizing casual restaurants such as fast food chains are food quality, service quality, atmosphere, and price (Mattila, 2001).

4.3 Customers’ Level of Loyalty

469 Marlon B. Raquel & Anthony Greg F. Alonzo The succeeding tables present the level of loyalty of customers towards the leading fast food chain.

Table 8 Customers’ Level of Loyalty in terms of Repurchase Intention

Repurchase Intention Weighted Standard Verbal Inter- Rank Mean Deviation pretation 1. I would visit this store again. 3.32 .662 Strongly Agree 1 2. If I got any product for free, I would still 3.30 .672 Strongly Agree 3 buy product from this store. 3. I would eat in this store the next time. 3.31 .672 Strongly Agree 2 4. I will continue to patronize the products 3.18 .676 Agree 4 and services of this store in the future. 5. I will buy other products and services be- 3.12 .702 Agree 5 ing offered in this store. Composite Mean 3.25 Strongly Agree

Table 8 indicates that respondents’ level of loyalty is very high as shown in the degree by which they agree on the repurchase intention indicators with composite mean of 3.25 and its verbal interpretation of ‘strongly agree’. In fact, respondents are likely to visit the store again (WM=3.32) which ranks first. They are also more likely to eat at the store the next time around (WM=3.31) which ranks second among five indicators of repurchase intention. Even if they are offered with a free product, they would still buy products of the fast food store (WM=3.30) which ranks third. Not only products of the fast food store will be patronized by the respondents but services as well (WM=3.18). This leading fast food store offers birthday party packages to those who wish to celebrate the occasion at the store. Likewise, customers are willing to buy other products and services offered by the store (WM=3.12). The first three indicators have verbal interpretations of ‘strongly agree’ while the last two indicators have descriptive interpretations of ‘agree’ which are indicative that customers would still come back to the store and make purchases of store’s products and services in the future.

Table 9 Customers’ Level of Loyalty in terms of Word-of-Mouth

Word-of-Mouth Weighted Standard Verbal Rank Mean Deviation Interpretation 1. I would say positive things about this 3.16 .694 Agree 1 store to other people. 2. I would encourage my friends, relatives, 3.14 .744 Agree 2 and colleagues to eat in this fast food. 3. I would recommend this store as the best 3.02 .732 Agree 5 fast food store. 4. I can say that this store makes me satis- 3.10 .669 Agree 3 fied. 5. I will say positive reviews to people about 3.08 .685 Agree 4 this store. Composite Mean 3.10 Agree

As can be seen in Table 9, the overall rating of the level of customer loyalty in terms of word-of-mouth indicators is 3.10 and interpreted as ‘agree’. Among the indicators mentioned, customers agreed that they would say positive things about the store to other people with a weighted mean of 3.16, the highest among the five. Customers would also encourage their friends, relatives, and colleagues to eat in the same fast food having a weighted mean of 3.14.

470 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines They also agreed that the store made them satisfied (WM=3.10), they will say positive re- views to people about the store (WM=3.08), and they would recommend the store as the best fast food store (WM=3.02).

Table 10 Customers’ Level of Loyalty in terms of First-in-Mind

First-in-Mind Weighted Standard Verbal Inter- Rank Mean Deviation pretation 1. If I would eat in a fast food restaurant 3.02 .735 Agree 2 again tomorrow, this store would be my first choice. 2. When talking about fast food, I think of 2.96 .817 Agree 5 this store first. 3. Even with the presence of new competi- 2.97 .764 Agree 4 tors, I will dine in this fast food store first. 4. The offering of discounts from other fast 2.98 .739 Agree 3 food stores will not change my mind to prior- itize first this store. 5. I think of this store first when talking 3.17 .742 Agree 1 about burgers and spaghetti. Composite Mean 3.02 Agree

Table 10 shows customers’ level of loyalty in the leading fast food store in terms of first-in-mind indicators. When asked about their degree of agreement or disagreement on the statement ‘I think of this store first when talking about burgers and spaghetti’, respondents said that they agree as manifested by mean score of 3.17 which ranks first. This is followed by the statement ‘If I would eat in a fast food restaurant again tomorrow, this store would be my first choice’ with a weighted mean of 3.02. The third rank has a mean of 2.98 which re- fers to the statement ‘The offering of discounts from other fast food stores will not change my mind to prioritize first this store.’ Even with the presence of new competitors, customers said they will dine in fast food store first as shown in the weighted mean of their responses which is 2.97 which ranks fourth. Finally, when customers talk about fast food stores, they think this leading store first with a weighted mean of 2.96.

Table 11 Composite Mean Scores of Customer Loyalty

Customer Loyalty Weighted Mean Verbal Rank Interpretation Repurchase Intention 3.25 Agree 1 Word-of-Mouth 3.10 Agree 2 First-in-Mind 3.02 Agree 3 Composite Mean 3.12 Agree

Mean scores of customer loyalty indicators are shown in Table 11. As seen in the table above, each of the three indicators has a weighted mean that falls under the descriptive inter- pretation of ‘agree’. Customers agree that they have the intention to repurchase products from the store with a weighted mean of 3.25, followed by word-of-mouth with a weighted mean of 3.10, and lastly the first-in-mind indicator with a weighted mean of 3.02. With a composite mean of 3.12 and a verbal interpretation as ‘agree’, this means customers are loyal to the leading fast food store under study.

471 Marlon B. Raquel & Anthony Greg F. Alonzo

Table 12 Correlations Matrix of Socio-demographic Profile and Customer Satisfaction

Socio-demographic Profile Customer Satisfaction Gender Education Age Income

Food Quality -.008 .026 .006 -.121* Service Quality .039 .087 .096 -.130** Physical Environment .024 .025 -.041 -.042 Price/Perceived Value .037 .046 .087 -.060 for Money Interpretation Not signif- Not signif- Not signif- Significant for Food Quality & Ser- icant icant icant vice Quality; Not significant for Physical Environment & Price/ Perceived Value for Money *Correlation is significant at 0.05 level of significance. ** Correlation is significant at 0.01 level of significance.

In measuring the relationship between customer satisfaction and customer loyalty, Spearman’s rho correlation was used. All but one socio-demographic characteristic resulted to a significant relationship with two customer satisfaction indicators. This study revealed that income of customers and food quality has significant relationship with r-value of -.121. The relationship between service quality and income was also significant at 0.01 alpha level with r-value of -.130. Thus, statistical significance exists at 0.05 level of significance.

Table 13 Correlations Matrix between Socio-demographic Profile and Customer Loyalty

Socio-demographic Profile Customer Loyalty Gender Education Age Income Repurchase Intention .082 .110* .046 -.029 Word-of-Mouth .110* .098* .014 -.108* First-in-Mind .109* .032 -.017 -.093 Interpretation Significant for Significant for Not signifi- Significant for Word-of-Mouth Repurchase cant Word-of-Mouth; & First-in- Intention & Not significant for Mind; Not sig- Word-of- Repurchase Inten- nificant for Re- Mouth; Not tion & First-in-Mind purchase Inten- significant for tion First-in-Mind *Correlation is significant at 0.05 level of significance.

Table 13 shows the relationships among the socio-demographic characteristics and five indicators of customer loyalty. Gender did not show any significant relationship to repurchase intention, thus, hypothesis is accepted. Word-of-mouth and first-in-mind indicators, however, were significant to gender. As to education, only its relationship with first-mind indicator was insignificant. The educational attainment of respondents was statistically significant to repur- chase intention and word-of-mouth at 0.05 level of significance. No customer loyalty indica- tors was found to be significant to age. As for income, only the word-of-mouth indicator was found to be significant.

472 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines

Table 14 Correlations Matrix of Customer Satisfaction and Customer Loyalty

Customer Satisfaction Customer Loyalty Price/ Food Quality Service Quality Physical Perceived Value for Environment Money Repurchase .634** .602** .538** .584** Intention Word-of-Mouth .590** .620** .543** .519** First-in-Mind .541** .576** .525** .473** Interpretation Significant Significant Significant Significant **Correlation is significant at 0.01 level of significance.

As shown in Table 14, customer satisfaction is highly correlated with customer loyalty. The values of correlation coefficients are high in all variables. The highest of these is the re- lationship between food quality and repurchase intention with r-value of 0.634. This is fol- lowed by service quality and word-of-mouth (0.620), service quality and repurchase intention (0.602), food quality and word-of-mouth (0.590), price/perceived value for money and repur- chase intention (0.584), service quality and first-in-mind (0.576), physical environment and word-of-mouth (0.543), food quality and first-in-mind (0.541), physical environment and re- purchase intention (0.538), physical environment and first-in-mind (0.525), and price and word-of-mouth (0.519). The least strength of correlations was found between price and first- in-mind indicator. Customers agreed that food offered has different menu, pleasing appearance, clean, good taste, and excellent quality and these affect their loyalty. Excellent food quality leads them to return to the same fast food store and patronize their products and services.

5 Discussion of Findings

5.1 Profile of the Respondents

Majority of the respondents are young (10 to 29 years old) with a combined sample of 80.8%. There were more females than male respondents (63.0% vs. 37.0%). Most respond- ents have bachelor’s degrees that comprise 64.5% of the total sample size. About 40% of the respondents have incomes between P10,000 and P20,000 per month.

5.2 Levels of Customer Satisfaction

The levels of customer satisfaction were measured using the weighted means of cus- tomers’ responses of Likert scale items. Respondents generally agreed, which means satis- fied, to the leading fast food store as shown in the composite mean score of 3.00. Among 20 indicators of customer satisfaction, good taste of food has the highest level of satisfaction ex- perienced by the customers with weighted mean of 3.42 out of 4.00. However, it appears that they disagreed, that is, dissatisfied when asked about physical environment. It implies that customers were not satisfied with the physical environment of the store. Food quality ranks first, followed by price, service quality, and physical environment. Perceived quality of food remains the number one concern for the customers, outdoing price of products.

473 Marlon B. Raquel & Anthony Greg F. Alonzo As shown in the results of the study, age, gender, and education did not show signifi- cant relationships with customer satisfaction. For income, only the food quality and service quality were found to be significant to customer satisfaction. This only shows that customers put premium to the quality of food they eat and the quality of service they receive every time they dine in at fast food stores. When tested further using the overall measure of customer satisfaction, the findings reinforce the results that these socio-demographic characteristics are not significant to the level of satisfaction of customers.

5.3 Levels of Customer Loyalty

Among the three indicators of customer loyalty, repurchase intention ranks first which means customers will be returning to dine in the fast food restaurant. This is followed by word-of-mouth marketing where customers would say good things about the store to other people. Lastly, first-in-mind ranks third. Customers were generally loyal to the fast food store as shown by the composite mean of 3.00 with the verbal interpretation of ‘agree’. Because of so many fast food stores and other small businesses, competition is so fierce that one needs to formulate marketing strategies that would be beneficial to everyone.

5.3 Correlations between Profile of Respondents and Customer Satisfaction

The findings of this research show that generally, socio-demographic characteristics of respondents did not show significant correlations with the overall measure of customer satis- faction. However, income is statistically significant with both food quality and service quality which are negatively associated. This is consistent with the findings of previous studies such as Sivesan and Karunanithy (2013) who found that customers who have higher incomes tend to scrutinize the quality they receive from fast food restaurants. While gender was found to have a significant relationship with customer satisfaction in the study of Abdullah and Hamdan (2012), the study of Raza et al (2012) found no significant relationship between the two variables. The study of Raza was confirmed in this particular study that gender does not have any significance with customer satisfaction.

5.4 Correlations between Profile of Respondents and Customer Loyalty

Household income is believed to be positively influence the level of customer loyalty (Keaveney & Parthasarathy, 2001; Verboef & Donkers, 2005). Customers that are more con- cerned with prices tend to be less loyal because lower household incomes lead to increased price comparisons, thus, lowers loyalty. These findings are partly true in this research. This study reveals that income and word-of-mouth indicator were correlated but income and other loyalty indicators were not. However, Shankar et al (2003) provided opposite conclusions: higher income customers tend to be more loyal. The discrepancy in different researches, in- cluding this work, on the relationship of income to customer loyalty is worth noting. Further researches are recommended. Existing research (Mittal & Kamakura, 2001) has also been consistent with the fact that higher levels of education are associated with lower levels of loyalty. As education levels in- creases, so does the customers’ need for information related to their purchase intention, thereby increasing purchasing involvement. This association between educational levels and purchasing involvement suggests that educational levels should be negatively associated with loyalty. However, this research shows that education and customer loyalty were not statisti- cally significant.

474 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines Based on the results of the study, age did not exhibit any significant relationship with any of the customer loyalty indicator. Even after testing the correlation between age and the overall customer loyalty, it did not exhibit any significant relationship. This means age does not matter to being loyal in the fast food store. Results also show that gender, education, and income of respondents have significant relationships with word-of-mouth indicator, which means, customers would usually tell other people such as their families, friends, and col- leagues about positive reviews of the store. Gender and first-in-mind indicator also manifest- ed significant relationship. It means thoughts about making the fast food store a priority dif- fers whether a customer is a male or female. Difference in educational attainment is found to be significant with the customers’ intention for return patronage. When correlations are run using the overall measure of customer loyalty, none of the socio-demographic characteristics exhibited significant relationship.

5.5 Correlations between Customer Satisfaction and Customer Loyalty

Findings of this study show that customer satisfaction and customer loyalty are highly correlated at significant level 0.05. This is consistent with the previous studies. Sefian et al (2013) showed that customers revisit the fast food outlets due to the food quality and per- ceived value offered by them. Ryu and Han (2010) confirmed that providing high-quality food is a key component of running a successful quick-casual restaurant. All indicators of customer satisfaction and customer loyalty were found be highly sig- nificant.

6 Conclusions and Recommendations

In any business organization, customer satisfaction is one of the most important issues (if not the most important of them all) that business organizations need to be addressed. Cus- tomer satisfaction is an integral concept in marketing and the key element in planning, organ- izing, and implementing marketing activities. When customers are satisfied, customers are likely to return and continue patronizing the fast food industry’s products and services. Therefore, market researchers and managers need to look closely at issues which affect cus- tomer satisfaction. In this study, four socio-demographic variables were used to describe the characteristics of customers by means of frequencies and percentages. These profile characteristics are age, gender, educational attainment, and income. Majority of the customers are young, female, have bachelor’s degrees, and earn between P10,000 and P20,000 monthly. Levels of satisfaction and loyalty were measured by using means of Likert scale items. Customers of the fast food store are generally satisfied with the quality of food, service quali- ty, and perceived value for money on one hand. On the other hand, they are generally dissat- isfied with the physical environment of the store. However, customers agree that they would still be loyal to the fast food store. In the end, it is concluded that food quality, service quality, physical environment, and price/perceived value for money are significantly correlated with repurchase intention, word- of-mouth, and first-in-mind – indicators of customer loyalty. Significant positive relationship between customer satisfaction and customer loyalty is established. Managers of any fast food restaurant should be cognizant of the needs and wants of the customers and offer them quality in all aspects of the business. Enhanced policies and guide- lines should be designed to improve the service quality and physical environment of the store such as the following:

475 Marlon B. Raquel & Anthony Greg F. Alonzo 1. Respond to customer feedback and/or satisfaction surveys as honest as possible. Customer feedback and satisfaction surveys are very important to determine the level of satisfaction of customers which would eventually be useful for the man- agement. Customers, therefore, should answer questions as honest as possible and make it sure that they would return the questionnaires with complete answers. Cus- tomers should understand that their opinions matter and these serve as starting point for companies to offer new products, improve existing products and services, and offer retention plans. 2. Continued preparation of high-quality of food is important. Food quality was the top reason why customer satisfaction was very high, therefore, owners or operators of this leading fast food store must continue preparing food that is good-tasting and has high quality. Researches show that quality of food greatly influences the level of customer satisfaction. Marketing researches must be conducted what particular menu the customers want, launch the product for market test, and evaluate whether or not customers want it. Owners must not be afraid of innovation. Managers must modernize food preparation and food technology. 3. Intensive marketing for the existing loyalty program must be pursued. As re- vealed by the results of this study and consistent with previous researches, custom- ers of fast food stores and other casual quick service restaurants put premium to the value of money they used in exchange for patronizing the companies’ products and services. While the fast food store currently offers a loyalty card where customers earn points every time they make purchases, it has not been introduced intensively to customers. For instance, P50 worth of purchase is equivalent to one point, which in turn, is equal to P1.00 (in contrast to one point for every P200 worth of products in other competitors). Some customers have expressed their satisfaction on loyalty card because it adds value to their money. The researcher also recommends partner- ship with banks and other merchants so that customers would be able to use these cards in transactions with other partner stores. Many loyalty cards today have part- nered with MasterCard and/or Visa so that their loyalty cards serve as debit cards which can be used for online shopping. 4. Service quality must be improved. Service quality ranks second lowest among the four indicators of customer satisfaction. While customers are generally satisfied with service quality, two important indicators exhibited the lowest intensity of satis- faction. These are the provision of quick service and the willingness and ability of service crews to provide that service in a timely manner. One possible reason for this is the long queues when ordering food. It is recommended that when long queues are observed, all point-of-sale (POS) machines must be operated. Service crews must also learn to smile with consistency to customers who are being served as this shows hospitality service. 5. Maintain cleanliness of the physical environment of the store. Based on the com- posite mean scores of the respondents, physical environment has the lowest mean score which means customers are not satisfied. Majority of the comments written by customers in the survey questionnaire identified comfort rooms as ‘dirty’ and ‘needs improvement.’ While customers are satisfied with the quality of food, dissat- isfaction with physical environment may result to a decrease in loyalty. Comfort rooms must have adequate supply of water, liquid hand soaps, and tissue papers. Outside surroundings must always be cleaned so that garbage would not be a sore in the customers’ eyes. Place or location is one of the most important elements in 7Ps of marketing mix. Therefore, marketing strategy of this leading fast food store should focus more on cleanliness of the physical environment. One way of doing this is to conduct intensive orientation among service crews especially those who

476 An Inter-correlational Study on Socio-demographic Profile, Customer Satisfaction and Customer Loyalty in a Fast Food Restaurant in the Philippines are assigned to clean dining areas, comfort rooms, and proximities. Managers should regularly check comfort rooms and other areas to make sure that assigned personnel are doing their jobs properly. 6. Offer cash discounts for meals. Pricing strategies are very important in a competi- tive market. Based on the findings of this study, price/perceived value for money is highly correlated with customer loyalty. Therefore, fast food store must continue of- fering value meals, freebies, and cash discounts for purchases. 7. The use of different forms of advertising is highly recommended. To increase the chance of customers’ acceptance of the fast food’s products and services, different media mixes must be utilized. For instance, tarpaulins (billboards) must be conspic- uously displayed in the surroundings. A TV monitor would also help customers know more about their product and service offerings.

7 Implications for Future Research

Examining the effects of predictor variables to both customer satisfaction and customer loyalty. To examine the effect of variables under studied to customer satisfaction and cus- tomer loyalty, the proponent recommends further studies. What are the variables that affect satisfaction and loyalty? To what extent do these variables affect the dependent variables? These questions are worth exploring and regression analysis would tell us the degree of effect of predictors to the dependent variables. Conducting research studies on the same fast food store but in different locations is suggested. Generally, it was found in this study that socio-demographic variables are not cor- related with either satisfaction or loyalty variable. Will this finding be also true to fast food stores of similar brand but are located in different place such as in business districts, e.g. Bonifacio Global City ? This would validate or invalidate the findings presented in the current study. Comparative studies of customer satisfaction and loyalty of different brand names/companies are highly recommended. In comparing how customers perceive satisfac- tion and loyalty in different fast food stores albeit different brand names gives the researchers an idea whether or not the same set of customer characteristics affect satisfaction and loyalty. Moreover, to know the needs of customers and to satisfy them, managers and restaurant administration should study customer’s values and must understand how consumers perceive their restaurant’s products and services, so a study that divulges consumer perception of all brands is necessary. A study of this type should explain how customers appraise main brands that help in the managerial and the academic understanding of customers’ assessment pro- cess. Restaurants should invest in the training and development of their employees as they are the ones who are directly dealing with the customers. Their presence and approach creates an image in the customers mind. Customer retention is important in the current competitive en- vironment. Restaurant manager should need to take care of the factors that directly impact the customer retention rate. As what F.P. Reichheld said, "As a customer's relationship with the company lengthens, profits rise. And not just by a little. Companies can boost profits by al- most 100 percent by retaining just 5 percent more of their customers". Managers must always bear this in mind.

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• Corpus ID: 202598975

Customer Loyalty in the Fast Food Industry in the Philippines

• Marlon B. Raquel
• Published 2017
• Business, Economics

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• Consumer price index (CPI) of food Philippines 2018-2023

In 2023, the consumer price index (CPI) for food in the Philippines was 125.01. This was an increase by about nine index points compared to the previous year. The CPI is a measure of the average change over time in the prices paid by consumers for consumer goods.

Consumer price index (CPI) for food in the Philippines from 2018 to 2023

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August 2024

Philippines

2018 to 2023

Base year 2018 = 100.

Other statistics on the topic FMCG market in the Philippines

• Household expenditure on alcoholic beverages and tobacco Philippines 2017-2023

Food & Nutrition

• Price of basic food products Philippines 2022-2024
• Household final consumption expenditure Philippines 2023, by purpose
• Dairy & dairy substitute brand preference Philippines 2023, by CRP

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Statistics on " FMCG market in the Philippines "

• YoY growth rate FMCG value Asia Q3 2018-Q2 2023, by country
• YoY growth rate FMCG value Asia Q3 2018-Q2 2023, by segment
• YoY growth rate FMCG value Philippines Q1 2023-Q1 2024, by segment
• Major FMCG sales channels Philippines Q1 2024, by market share
• Food market revenue change in the Philippines 2020-2029, by type
• Sales volume of the food market in the Philippines 2023, by type
• Production index volume in food products manufacturing Philippines 2018-2023
• Household consumption expenditure food and non-alcoholic drinks Philippines 2017-2023
• Food retail sales value Philippines 2022, by outlet type
• Philippines: revenue growth of non-alcoholic drinks market 2023-2027, by type
• Philippines: sales volume of non-alcoholic drinks market 2014-2027
• Sales channels of non-alcoholic drinks Philippines 2021-2029
• Consumer price index (CPI) of non-alcoholic beverage Philippines 2018-2023
• Import value of coffee Philippines 2012-2022
• Growth of alcoholic drinks revenue in the Philippines 2015-2027, by type
• Philippines: volume of the alcoholic drinks market, 2018-2028
• Sales channels of alcoholic drinks Philippines 2021-2029
• Consumer price index (CPI) of alcoholic beverage Philippines 2018-2023
• Price per unit of alcoholic drinks Philippines 2024, by type
• Beauty & personal care market sales channel share in the Philippines 2019-2027
• YoY value growth personal care segment Philippines Q1 2020-Q3 2023
• Consumer price index (CPI) of personal care Philippines 2018-2023
• Import value of cosmetic products Philippines 2013-2023
• Personal care products used regularly Philippines 2024, by type
• Pet food retail sales value Philippines 2020-2029
• Pet food retail sales value Philippines 2023, by category
• Market share of pet food retail channels Philippines 2023, by outlet type
• Import value of dog and cat food products Philippines 2018-2023
• Revenue of San Miguel Food and Beverage Inc FY 2018-FY 2023
• Revenue of Nestlé Philippines FY 2019- FY 2023
• Universal Robina Corporation net sales FY 2017-FY 2023
• Gross revenue of Monde Nissin Corporation FY 2019- FY 2023
• FMCG brand preferences Philippines 2023, by CRP
• Food brand preference Philippines 2023, by CRP
• Beverage brand preference Philippines 2023, by CRP
• Home care brand preference Philippines 2023, by CRP
• Personal care brand preference Philippines 2023, by CRP

Other statistics that may interest you FMCG market in the Philippines

• Premium Statistic YoY growth rate FMCG value Asia Q3 2018-Q2 2023, by country
• Premium Statistic YoY growth rate FMCG value Asia Q3 2018-Q2 2023, by segment
• Premium Statistic YoY growth rate FMCG value Philippines Q1 2023-Q1 2024, by segment
• Premium Statistic Household final consumption expenditure Philippines 2023, by purpose
• Premium Statistic Major FMCG sales channels Philippines Q1 2024, by market share

Key segment: Food

• Premium Statistic Food market revenue change in the Philippines 2020-2029, by type
• Premium Statistic Sales volume of the food market in the Philippines 2023, by type
• Premium Statistic Production index volume in food products manufacturing Philippines 2018-2023
• Premium Statistic Household consumption expenditure food and non-alcoholic drinks Philippines 2017-2023
• Premium Statistic Consumer price index (CPI) of food Philippines 2018-2023
• Premium Statistic Food retail sales value Philippines 2022, by outlet type
• Basic Statistic Price of basic food products Philippines 2022-2024

Key segment: Non-alcoholic beverage

• Premium Statistic Philippines: revenue growth of non-alcoholic drinks market 2023-2027, by type
• Premium Statistic Philippines: sales volume of non-alcoholic drinks market 2014-2027
• Premium Statistic Sales channels of non-alcoholic drinks Philippines 2021-2029
• Premium Statistic Consumer price index (CPI) of non-alcoholic beverage Philippines 2018-2023
• Premium Statistic Import value of coffee Philippines 2012-2022

Key segment: Alcoholic beverage

• Premium Statistic Growth of alcoholic drinks revenue in the Philippines 2015-2027, by type
• Premium Statistic Philippines: volume of the alcoholic drinks market, 2018-2028
• Premium Statistic Sales channels of alcoholic drinks Philippines 2021-2029
• Premium Statistic Household expenditure on alcoholic beverages and tobacco Philippines 2017-2023
• Premium Statistic Consumer price index (CPI) of alcoholic beverage Philippines 2018-2023
• Basic Statistic Price per unit of alcoholic drinks Philippines 2024, by type

Key segment: Cosmetics and personal care

• Premium Statistic Beauty & personal care market sales channel share in the Philippines 2019-2027
• Premium Statistic YoY value growth personal care segment Philippines Q1 2020-Q3 2023
• Premium Statistic Consumer price index (CPI) of personal care Philippines 2018-2023
• Premium Statistic Import value of cosmetic products Philippines 2013-2023
• Premium Statistic Personal care products used regularly Philippines 2024, by type

Key segment: Pet food

• Premium Statistic Pet food retail sales value Philippines 2020-2029
• Premium Statistic Pet food retail sales value Philippines 2023, by category
• Premium Statistic Market share of pet food retail channels Philippines 2023, by outlet type
• Premium Statistic Import value of dog and cat food products Philippines 2018-2023

Market leaders

• Premium Statistic Revenue of San Miguel Food and Beverage Inc FY 2018-FY 2023
• Premium Statistic Revenue of Nestlé Philippines FY 2019- FY 2023
• Premium Statistic Universal Robina Corporation net sales FY 2017-FY 2023
• Premium Statistic Gross revenue of Monde Nissin Corporation FY 2019- FY 2023

Brand preference

• Premium Statistic FMCG brand preferences Philippines 2023, by CRP
• Premium Statistic Food brand preference Philippines 2023, by CRP
• Premium Statistic Beverage brand preference Philippines 2023, by CRP
• Premium Statistic Home care brand preference Philippines 2023, by CRP
• Premium Statistic Dairy & dairy substitute brand preference Philippines 2023, by CRP
• Premium Statistic Personal care brand preference Philippines 2023, by CRP

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Voluntary Sodium Reduction Goals: Target Mean and Upper Bound Concentrations for Sodium in Commercially Processed, Packaged, and Prepared Foods; Draft Guidance for Industry (Edition 2); Availability

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• Document Details Published Content - Document Details Agencies Department of Health and Human Services Food and Drug Administration Agency/Docket Number Docket No. FDA-2014-D-0055 Document Citation 89 FR 66727 Document Number 2024-18261 Document Type Notice Pages 66727-66729 (3 pages) Publication Date 08/16/2024 Published Content - Document Details
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Voluntary Sodium Reduction Goals: Target Mean and Recommended Maximum Concentrations for Sodium in Commercially Processed, Packaged, and Prepared Foods

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• [Docket No. FDA-2014-D-0055]

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Notice of availability.

The Food and Drug Administration (FDA or we) is announcing the availability of a draft guidance for industry entitled “Voluntary Sodium Reduction Goals: Target Mean and Upper Bound Concentrations for Sodium in Commercially Processed, Packaged, and Prepared Foods (Edition 2).” The draft guidance, when finalized, will describe our views on the next voluntary goals (Phase II (3-year)) for sodium reduction in a variety of identified categories of foods that are commercially processed, packaged, or prepared. These goals are intended to address the excessive intake of sodium in the current population to help reduce the burden of diet-related chronic disease, promote improvements in public health, and advance health equity by supporting a healthier food supply.

Submit either electronic or written comments on the draft guidance by November 14, 2024 to ensure that we consider your comment on the draft ( print page 66728) guidance before we begin work on the final version of the guidance.

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Instructions: All submissions received must include the Docket No. FDA-2014-D-0055 for “Voluntary Sodium Reduction Goals: Target Mean and Upper Bound Concentrations for Sodium in Commercially Processed, Packaged, and Prepared Foods (Edition 2).” Received comments will be placed in the docket and, except for those submitted as “Confidential Submissions,” publicly viewable at https://www.regulations.gov or at the Dockets Management Staff between 9 a.m. and 4 p.m., Monday through Friday, 240-402-7500.

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Submit written requests for single copies of the draft guidance to the Office of Food Additive Safety, Center for Food Safety and Applied Nutrition, Food and Drug Administration, 5001 Campus Dr., College Park, MD 20740. Send two self-addressed adhesive labels to assist that office in processing your request. See the SUPPLEMENTARY INFORMATION section for electronic access to the draft guidance.

Kasey Heintz, Center for Food Safety and Applied Nutrition, Office of Food Additive Safety, Food and Drug Administration, 5001 Campus Dr., College Park, MD 20740, 240-402-1376; or Holli Kubicki, Center for Food Safety and Applied Nutrition, Office of Regulations and Policy, Food and Drug Administration, 5001 Campus Dr., College Park, MD 20740, 240-402-2378.

We are announcing the availability of a draft guidance for industry entitled “Voluntary Sodium Reduction Goals: Target Mean and Upper Bound Concentrations for Sodium in Commercially Processed, Packaged, and Prepared Foods (Edition 2).” We are issuing the draft guidance consistent with our good guidance practices regulation ( 21 CFR 10.115 ). The draft guidance, when finalized, will represent the current thinking of FDA on this topic. It does not establish any rights for any person and is not binding on FDA or the public. You can use an alternate approach if it satisfies the requirements of the applicable statutes and regulations.

Sodium is widely present in the American diet (most commonly, but not exclusively, as a result of eating or drinking foods to which sodium chloride, commonly referred to as “salt,” has been added). More than 70 percent of total sodium intake is from sodium added during food manufacturing and commercial food preparation (Ref. 1). The average sodium intake for those 1 year and older in the United States is approximately 3,400 milligrams/day (mg/day) (Ref 2). The “Dietary Guidelines for Americans, 2020-2025” (Ref. 2) advises individuals 14 years and older to limit their consumption to 2,300 mg/day; this aligns with recommendations from the National Academies of Sciences, Engineering, and Medicine, which set the chronic disease risk reduction intake for sodium at 2,300 mg/day for those 14 years and older (Ref. 3). The guidance aims to help Americans reduce average sodium intake to 2,750 mg/day (Phase II) by encouraging food manufacturers, restaurants, and food service operations to gradually reduce sodium in a wide variety of food categories over time. Although we recognize that a reduction even to 2,750 mg/day still would be higher than the recommended sodium limit of 2,300 mg/day, the Phase II goals are intended to balance the need for broad and gradual reductions in sodium and what is publicly known about technical and market constraints on sodium reduction and reformulation.

In the Federal Register of October 14, 2021, we announced the availability of the final guidance for industry, “Voluntary Sodium Reduction Goals: Target Mean and Upper Bound Concentrations for Sodium in Commercially Processed, Packaged, and Prepared Foods” ( 86 FR 57156 ). The ( print page 66729) draft guidance builds on the voluntary Phase I (2.5-year) sodium reduction goals issued in October 2021. When finalized, the draft guidance will describe our views on the next voluntary goals (Phase II (3-year)) for sodium reduction in a variety of identified categories of foods that are commercially processed, packaged, or prepared. The 3-year goals are intended to balance the need for broad and gradual reductions in sodium and what is publicly known about technical and market constraints on sodium reduction and reformulation. The distribution of sodium concentrations in currently available products in each category was a significant factor in developing these quantitative sodium concentration goals. We developed the goals with a particular emphasis on maintaining concentrations needed for food safety, given the function of salt as a food preservative. The Phase II goals are within the range of concentrations found in currently marketed foods and are feasible using existing technical strategies.

We note that we do not intend to finalize the draft long-term (10-year) sodium reduction goals that were included in the 2016 draft of the first edition of the guidance that we announced in the Federal Register of June 2, 2016 ( 81 FR 35363 ). We plan to announce any future sodium reduction goals via draft guidance.

While the guidance contains no collection of information, it does refer to previously approved FDA collections of information. The previously approved collections of information are subject to review by the Office of Management and Budget (OMB) under the Paperwork Reduction Act of 1995 (PRA) ( 44 U.S.C. 3501-3521 ). The collections of information in 21 CFR part 101 have been approved under OMB control number 0910-0381. The collections of information in 21 CFR 101.11 have been approved under OMB control number 0910-0782.

Persons with access to the internet may obtain the draft guidance at https://www.fda.gov/​FoodGuidances , https://www.fda.gov/​regulatory-information/​search-fda-guidance-documents , or https://www.regulations.gov . Use the FDA website listed in the previous sentence to find the most current version of the guidance.

The following references are on display at the Dockets Management Staff (see ADDRESSES ) and are available for viewing by interested persons between 9 a.m. and 4 p.m., Monday through Friday; they are also available electronically at https://www.regulations.gov . Although FDA verified the website addresses in this document, please note that websites are subject to change over time.

1. Harnack L.J., M.E. Cogswell, J.M. Shikany, et al. “Sources of Sodium in U.S. Adults From 3 Geographic Regions.” Circulation, 135 (May 9, 2017): pp. 1775-1783. Available at: https://www.ahajournals.org/​doi/​10.1161/​CIRCULATIONAHA.116.024446 (accessed December 26, 2023).

2. U.S. Department of Agriculture and U.S. Department of Health and Human Services. “Dietary Guidelines for Americans, 2020-2025.” 9th Edition. December 2020. Available at: https://www.dietaryguidelines.gov/​ (accessed December 26, 2023).

3. National Academies of Sciences, Engineering, and Medicine. “Dietary Reference Intakes for Sodium and Potassium” (March 2019). Washington, DC: The National Academies Press. Available at: http://www.nationalacademies.org/​hmd/​Reports/​2019/​dietary-reference-intakes-sodium-potassium.aspx (accessed December 26, 2023).

Dated: August 9, 2024.

Lauren K. Roth,

Associate Commissioner for Policy.

[ FR Doc. 2024-18261 Filed 8-15-24; 8:45 am]

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