Purchase Quality Research Articles

Abstract MP08: Targeted Healthy Food Incentives Influence Grocery Purchase Quality and Purchase of Targeted Foods: Results From the Randomized Controlled Crossover Smart Cart Study

Introduction: Incentives can increase healthy food purchases, but less is known about whether they improve dietary quality. The Smart Cart Study evaluated whether healthful food incentives based on customer preferences and purchase history increased grocery purchase quality and the proportion of spending on targeted foods. Hypothesis: Targeted incentives will increase grocery purchase quality as measured by the Grocery Purchase Quality Index- 2016 (GPQI) and percent spending on targeted healthful foods. Methods: Adults (n=224) who shopped at an independent supermarket for ≥50% of their groceries, participated in the store’s loyalty program, and completed study questionnaires were enrolled in summer 2018. All participants received a 5% loyalty card discount. The intervention group received targeted weekly coupons (~$10 value) with brief education to improve purchase quality for 13-weeks. A computerized study algorithm allocated targeted healthy food coupons to participants’ loyalty cards by using purchase history, dietary preferences, and diet quality. The control group received weekly brief education and occasional generic coupons. After a brief washout, the groups crossed over. GPQI-16 scores (range 0-75) were calculated from cumulative food purchasing data by comparing actual to recommended spending within 11 food groups, with higher scores reflecting higher purchase quality; % spending on targeted vs. all foods was also compared. Paired t-tests examined differences between groups. Results: Participants with extreme spending (i.e. top/bottom 1%) were excluded, leaving an analytic sample of 207 mostly white adults (95%), with mean age of 56 and 50% with household incomes ≥100K. The Table shows changes in GPQI-16 scores and % spending in the first 13-week intervention period, followed by the cross-over intervention period. Conclusions: Results from this pilot trial suggest that targeted healthy supermarket incentives are feasible and are promising tools to help improve diet quality and health.

Evaluating the effect of individually-targeted food incentives on grocery purchases: The smart cart study protocol for a randomized controlled cross-over trial

Background/AimsHealth stakeholders are interested in the promise of healthy food incentives to improve dietary quality. The Smart Cart Study tested whether targeting healthful food incentives based on customer preferences and purchase history was effective for improving grocery purchase quality. DesignRandomized controlled crossover design of 224 adults who shopped at an independent supermarket for ≥50% of their groceries, participated in the store's loyalty program, and completed validated diet and sociodemographic/behavioral questionnaires. Participants were randomized using 1:1 blocked randomization; all participants received a 5% discount on their purchases with their loyalty card. For the first 13-weeks, the intervention group received individually-targeted weekly coupons (valued up to $10) with brief nutrition education to improve grocery purchase quality. The study team developed healthy food coupons, and the study algorithm allocated targeted coupons to participants' loyalty cards using purchase history, dietary preferences/allergies, and baseline diet quality. Control participants received weekly untargeted nutrition education and occasional generic coupons. Following a 2–4 week washout period, the two groups crossed over. The primary study outcomes were purchases of targeted products and grocery purchase quality measured using the validated Grocery Purchase Quality Index-2016; the study was powered to detect a minimum 3% difference in purchase quality. ConclusionsThe Smart Cart Study tested a novel application of automated individually-targeted marketing using customer purchase history, dietary quality, and preferences to identify and deliver targeted incentives to improve grocery purchase quality. Future research could scale this program through collaboration between multiple stakeholders, including supermarkets, workplace wellness initiatives and insurance companies.

Online Marketing-Study on Customer Satisfaction and Relationship

Online advertising gives moment information about the item that we have to purchase and satisfy our everyday needs. The propensity for surfing the clients’ survey in the online networking is presently multi day’s normal highlights among the adolescents. The sharing of item exhibitions in the informal organization is urged by the advertisers to comprehend their clients’ fulfilment and additionally to know whether any trap is seen by the client. This will assist the maker with modifying/enhance the item likewise. The more general society connection the advertiser had with their clients will reflect in enhanced consumer loyalty, when clients audits were certain at that point rehash deals and new deals will extend exponentially. Presently, the general population in littler towns in India can approach purchase quality items and administrations like what individuals in the bigger urban communities approach through web based showcasing. It is evaluated around 60% of online customers would originate from past the main eight vast urban areas1. After the passage of JIO web supplier, rivalry turned out to be more increased and now clients can get to an enormous measure of information in reasonable expense. This expansion in web infiltration has extended the potential client pool and for the most part among Gen Ys2. Additionally, their simple winning limit offered opportunity to purchase their everyday necessities all alone form and satisfy their fantasies. Presently, they feel exceptionally advantageous to shop on the web, since it liberates them from specifically visiting to the store and uses their valuable time in some other fascinating occupations. It is the obligation of the advertisers to give the important item data to these surfers and have balanced contact to build open connection with them to support their business change proportion.

Determinants of Consumers’ Retention and Subjective Well-Being: A Sustainable Farmers’ Market Perspective

Farmers’ markets have received much attention in many countries, and the amount of research on farmers’ markets is gradually increasing. The consumption process of consumers at farmers’ markets include both economic and social aspects, but most past studies have only focused on a single aspect. The economic perspective mainly focuses on transaction issues such as purchase motives, quality, satisfaction, purchase behavior, and post-purchase behavior, whereas the social perspective focuses on the social relations and psychological feelings created when consumers go to markets. This study aimed to integrate the economic and social perspectives and analyze the relationships among product performance evaluation, relational capital, repurchase intention, and subjective well-being of consumers at farmers’ markets after their purchase experiences. I chose three recurrent farmers’ markets in Taiwan, obtained 358 valid samples, and performed structural equation modelling analysis. The results indicated that the economic product performance exerted a significant and positive influence on repurchase intention, but its influence on subjective well-being was not significant. In contrast, the social relational capital was found to be a positive and significant factor of both repurchase intention and subjective well-being. On the whole, relational capital is more important than product performance. The suggestions for practice were as follows. First, farmers’ markets have economic and social value and are thus worth being promoted by government agencies. Second, the managers of farmers’ markets should implement a set of management mechanisms to ensure product performance and also create a market atmosphere that facilitates social interactions between farmers and consumers.

Joint Quality Investment and Inventory Decisions for Perishable Items with Reference Quality Effect under the O2O Environment

Reference quality, as a benchmark against which the purchase quality of a product is judged, has an important impact on consumers’ purchase decision, especially perishable items. Thus, how to determine an appropriate quality investment and ordering strategies for perishable items to maximize retailers’ profit is an essential task. A joint dynamic quality investment and inventory replenishment problem for perishable items with consideration of reference quality effect is investigated, where the retailer sells its products using a combination of the offline and online stores, and the sales function is sensitive to products’ quality and consumers’ reference quality. The optimal control model is established to maximize the retailer’s total profit by making a joint quality and inventory strategy. The continuous time dynamic optimal quality investment and inventory replenishment strategies with reference quality effect are obtained by Pontryagin’s maximum principle. Numerical experiments are accounted for the key system parameters on the optimal strategies.

Geographic Differences in the Dietary Quality of Food Purchases Among Participants in the Nationally-Representative Food Acquisition and Purchase Study (FoodAPS) (P04-158-19)

ObjectivesGrocery purchases may serve as an objective measure of diet, but it is unclear whether the diet quality of grocery purchases reflect geographic and racial/ethnic disparities observed in existing nationally-representative individual-level data. This study evaluated whether geographic and racial/ethnic disparities exist in the dietary quality of grocery purchases in a nationally-representative sample of US households. MethodsGrocery purchasing data from 3961 households from the Food Acquisition and Purchase Study (FoodAPS) were used. Demographic data was self-reported, and 7-day dietary data was recorded with scanners; the Healthy Eating Index (HEI) 2015 was used to assess diet quality. Survey-weighted multivariable-adjusted regression with planned contrasts was used to examine whether HEI-15 scores differed according to geographic region (Northeast, West, South, Midwest) and whether there was effect modification by race/ethnicity (Non-Hispanic White (NHW), Non-Hispanic Black (NHB) and Hispanic). ResultsPrimary respondents were, on average, 50.6 years, NHW (70.3%), female (70.2%) and had attended some college (57.8%). The mean HEI-15 score was 54.7, and scores differed by geography (P < 0.05), with the highest scores in the West (57.0 ± 0.8) and lowest scores in the South (53.1 ± 0.8). The influence of region on HEI-15 scores varied by race/ethnicity (p-interaction = 0.015). Among NHW, households in the South had scores that were 3.2-points lower than in the West (50.4 ± 0.7 vs. 53.6 ± 0.8, P = 0.003). Southern NHB households also had lower diet quality than NHB households in the West (48.6 ± 1.5 vs. 56.7 ± 2.7, P = 0.01). Conversely, Hispanic households in the Midwest (47.5 ± 2.0) had lower diet quality than Hispanic households in the South (54.1 ± 0.9, P = 0.02). Diet quality only differed across race/ethnicity (versus the NHW referent group) in the South and Midwest where Hispanic households had higher diet quality than NHW (54.1 ± 0.9 vs. 50.4 ± 0.7, P = 0.007) in the South, but lower diet quality than NHW households in the Midwest (47.5 ± 2.0 vs 52.2 ± 0.6, P = 0.02). ConclusionsDisparities in grocery purchase quality exist across US geographic regions and are divergent across racial/ethnic groups, which may reflect issues related to acculturation or environmental-level factors that require further study. Funding SourcesThis research was supported by the Rhode Island Foundation.

Geographic Differences in the Dietary Quality of Food Purchases among Participants in the Nationally Representative Food Acquisition and Purchase Survey (FoodAPS).

Objective grocery transactions may reflect diet, but it is unclear whether the diet quality of grocery purchases mirrors geographic and racial/ethnic disparities in diet-related diseases. This cross-sectional analysis of 3961 households in the nationally representative Food Acquisition and Purchase Survey evaluated geographic and racial/ethnic disparities in grocery purchase quality. Respondents self-reported demographics and recorded purchases over 7 days; the Healthy Eating Index (HEI) 2015 assessed diet quality. Survey-weighted multivariable-adjusted regression determined whether there were geographic and racial/ethnic differences in HEI-15 scores. Respondents were, on average, 50.6 years, non-Hispanic white (NHW) (70.3%), female (70.2%), and had attended some college (57.8%). HEI-15 scores differed across geographic region (p < 0.05), with the highest scores in the West (57.0 ± 0.8) and lowest scores in the South (53.1 ± 0.8), and there was effect modification by race/ethnicity (p-interaction = 0.02). Regionally, there were diet disparities among NHW and non-Hispanic black (NHB) households; NHWs in the South had HEI-15 scores 3.2 points lower than NHWs in the West (p = 0.003). Southern NHB households had HEI-15 scores 8.1 points lower than Western NHB households (p = 0.013). Racial/ethnic disparities in total HEI-15 by region existed in the Midwest and South, where Hispanic households in the Midwest and South had significantly lower diet quality than NHW households. Heterogeneous disparities in the diet quality of grocery purchases by region and race/ethnicity necessitate tailored approaches to reduce diet-related disease.

Festival quality, self-connection, and bragging

Festivals provide opportunities for experiential consumption, attracting both first-time and repeat visitors. However, current understanding of the perceptual and behavioural differences between these groups remains incomplete. This study investigates how experiential purchase quality influences experience self-connection and braggart word-of-mouth, for both first-time and repeat visitors, using a mixed-method approach. The qualitative (n = 32) and quantitative (n = 909) results together reveal that the combinations of experiential purchase quality dimensions stimulating experience self-connection and braggart word-of-mouth in repeat visitors differ significantly from those for first-time visitors, emphasising the need for festival managers to pay close attention to how different visitor groups perceive and prioritise experiential purchase quality dimensions. The findings thus extend current understanding of how braggart word-of-mouth emerges in an experiential consumption context.

WIC Participation and Relative Quality of Household Food Purchases: Evidence from FoodAPS

We examine the effect of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) on the quality of household food purchases using the National Household Food Acquisition and Purchase Survey (FoodAPS) and propensity score matching. A healthy purchasing index (HPI) is used to measure nutritional quality of household food purchases. WIC foods explain the improvement in quality of food purchases, not self‐selection of more nutrition‐conscious households into the program. The improvement in purchase quality was driven entirely by WIC participating households who redeemed WIC foods during the interview week. There was no significant difference between WIC participants who did not redeem WIC foods and eligible nonparticipants. In this sample, there is no evidence that lack of access to clinics has adverse effects on participation nor is there evidence that HPI depends on supermarket access. A supervised machine learning process supports our main conclusion on the importance of WIC foods.

Abstract P097: Sociodemographic Differences in the Dietary Quality of Food Purchases Among Participants in the Nationally-Representative Food Acquisition and Purchase Study (FoodAPS)

Background: Self-reported dietary data may not accurately represent usual dietary intake. Grocery purchase records provide an objective measure of diet, but little research has explored whether the diet quality of grocery purchases reflects individual-level diet quality and whether it differentiates between groups with known differences in dietary quality. This study evaluated whether there are sociodemographic differences in the dietary quality of grocery purchases akin to those observed in existing individual-level national data. Hypothesis: The diet quality of grocery purchases will reflect trends observed with individual-level diet quality. Methods: Grocery purchasing data from 3,961 households in the nationally-representative Food Acquisition and Purchase Study (FoodAPS) were used. Dietary data was collected using hand scanners over 7-days, and demographic data was self-reported. The Healthy Eating Index (HEI) 2015 was used to determine grocery purchase quality, and multivariable-adjusted regression with Tukey adjustment or planned contrasts were used to determine whether HEI-15 scores differed according to food insecurity, Supplemental Nutrition Assistance Program (SNAP) participation, obesity within a household, race/ethnicity, and interactions between these variables. FoodAPS sample weights and Taylor series linearization method for variance estimation accounted for the complex sample design. Results: Primary respondents were, on average, 50.6 years, non-Hispanic White (70.3%), female (70.2%) and had attended some college (57.8%). The mean HEI-15 score was 54.7; 14.0% of households were food insecure and 12.7% received SNAP benefits. HEI-15 scores differed across all sociodemographic predictors (p&lt;0.05). Additionally, interactions (p&lt;0.1) were detected between SNAP participation and (1) food insecurity and (2) obesity within the household as well as race/ethnicity and obesity within the household. Food secure, non-SNAP households had higher HEI-15 scores than food insecure, SNAP participating households (53.9±0.5 vs. 50.3±0.7, p=0.007) in models adjusted for age, income, smoking, and education. Similarly, non-SNAP households without obesity present had significantly higher HEI-15 scores than all other households. Obesity presence within a household was associated with lower HEI-15 scores in non-Hispanic White (50.8±0.5 vs. 52.5±0.7, p=0.046), and Black households (48.8±1.5 vs. 53.1±1.4, p=0.018), but not Hispanic households (54.4±1.0 vs. 52.2±1.2, p=0.21). Conclusions: Disparities in the diet quality of grocery purchases reflect individual-level trends and vary based on sociodemographic factors. This analysis highlights the interrelationships between SNAP, food insecurity, race/ethnicity, and obesity within a household, demonstrating how the co-occurrence of risk factors may modify associations with diet quality.

Abstract P233: Correlations Between Grocery Purchase Quality Index Scores and Healthy Eating Index Scores Vary by Demographics and Shopping Habits

Introduction: The Grocery Purchase Quality Index (GPQI) is a new, objective diet quality index that assesses adherence of household grocery purchases to the US Dietary Guidelines. Currently, little is known about the correlation between the GPQI and other common diet quality metrics like the Healthy Eating Index (HEI), and whether shopper characteristics (e.g., demographics, shopping habits) influence the strength of this correlation and the utility of the GPQI as a tool for tracking diet quality. Hypothesis: The GQPI and HEI-2010 will be moderately correlated at baseline in a cohort of shoppers enrolled in a study testing strategies to promote healthier grocery purchases, and these correlations will vary by shopper characteristics. Methods: Data from 224 households recruited from a single medium-sized grocery store were analyzed. Eligible participants were ≥18y, the primary shopper of their household, and did ≥50% of household shopping at store. Participants completed a baseline (Aug-Oct 2018) validated online food frequency questionnaire (FFQ) and a questionnaire about demographics and shopping habits. HEI-2010 scores were calculated from FFQs and GPQI scores were calculated from 2-6 weeks of baseline purchasing data; higher scores reflected healthier diets. Correlations between HEI and GQPI scores (reported as percent of total score) were calculated in SAS 9.4 for the overall sample and by demographic characteristics and shopping habits of interest. Results: The sample was predominantly female (90%), older (mean age=55.6±13.7), and higher socioeconomic status (47.9% &gt;college degree, 49.7% household income &gt;$100k). The mean HEI score was 73.0±9.3% out of 100pts, the mean GQPI score was 54.5±11.4% out of 75pts, and the mean BMI was 25.4±4.6. The two scores were moderately correlated in the overall sample (r=0.31, p&lt;0.001); correlations were stronger in men (r=0.52, p=0.02), middle-income ($60-100k) households (r=0.51, p=0.001), and individuals with underweight (n=14, r=0.58, p=0.03), and obesity (r=0.39, p=0.04) and weaker in individuals with normal weight (r=0.28, p=0.003). The GPQI and HEI were not correlated for individuals with overweight (r=0.16) low-income (&lt;$60k) households (r=0.16) or for those who shopped at farmer’s markets within the past month (r=0.15) whereas individuals who shopped at other grocery or superstores (r=0.31-0.35) had correlations similar to the overall sample. Conclusion: These findings suggest that food purchasing data reflects the individual diet quality and may be a promising tool for evaluating and monitoring individual-level diet quality. Further research should explore influential demographics and shopping habits on the strength of the correlation between the GQPI and HEI to develop more accurate predictive models using objective household purchasing data as a proxy for individual-level intake.

ANALYSIS OF UKRAINE’S INTERNATIONAL TRADE IN THE EUROPEAN UNION

Ukraine's foreign trade is one of the most important means of increasing the state budget, and the European Union is the strongest global economic organization, the largest and best regional market in the world. Therefore, the study of the problems of economic cooperation between Ukraine and the EU in the context of wide and favorable access of domestic enterprises products to the EU markets is becoming increasingly important for achieving a strategic goal. This goal concludes the development of Ukraine`s economy and achievement of a rightful place in the international differentiation of labor. The article considered the socio-economic nature, role and importance of international trade; main problems and prospects of Ukraine's trade with the EU as well as its dynamics and structure, various methods which are applied to analyze the current state of foreign trade of Ukraine with the EU. In our work we analyzed the obstacles of trading between Ukraine and the EU, ways to overcome them and benefits of this trade. The application of the Free Trade Area between Ukraine and the EU contributes to the gradual expansion of Ukrainian export access to European markets under the Association Agreement. The execution of this agreement for Ukrainian business entities simplified the entry to the protected domestic market of EU Member States and gave the opportunity to realize its own competitive benefits in purchase quality and price. Under this Free Trade Agreement Ukraine assumed not only opportunities but also certain obligations on improvement of quality standards and product safety, implementation of reforms in the area of technical regulation, development of quality assurance system and safety food industry. The simplification of goods access to other markets is indirect benefit for Ukrainian manufactures. The entry to the EU markets with high level standards automatically indicates goods quality.

Development of the Healthy Purchase Index (HPI): a scoring system to assess the nutritional quality of household food purchases.

To develop an index to assess the nutritional quality of household food purchases based on food expenditures only. A database of monthly food purchases of a convenience sample of low-income households was used to develop the Healthy Purchase Index (HPI). The HPI is the sum of two sub-scores based on expenditure shares of food categories in total household food expenditure: the purchase diversity sub-score and the purchase quality sub-score. The first was adapted from an existing diversity score. The second integrated those food categories identified as the best predictors of the nutritional quality of purchases based on associations between expenditure shares of food categories and two nutritional quality indicators: the mean adequacy ratio (MAR) and the mean excess ratio (MER). Correlation between the HPI and a score assessing adherence to French dietary guidelines (PNNS-GSmod) was performed as a first validation.Setting/ParticpantsFood purchases of 112 households from deprived neighbourhoods of Marseille (France), participating in the Opticourses and Jassur projects (2012-2015). The purchase diversity sub-score reflects the presence in food purchases of five food categories: fruits, vegetables, starches, dairy products, and meat, fish &amp; eggs. The purchase quality sub-score is based on expenditure shares for fruit &amp; vegetables, added fats &amp; seasonings, sweet snacks, cheese, sugary drinks, refined grains and fish, as these were identified as predictors of the nutritional quality of purchases. The HPI was positively associated with the PNNS-GSmod (r s=0·378; P&lt;0·001). The HPI helps assess the healthiness of household food purchases.

The Grocery Purchase Quality Index-2016 Performs Similarly to the Healthy Eating Index-2015 in a National Survey of Household Food Purchases

BackgroundHousehold food purchases are potential indicators of the quality of the home food environment, and grocery purchase behavior is a main focus of US Department of Agriculture (USDA) nutrition education programs; therefore, objective measures of grocery purchases are needed. ObjectiveThe objective of the study was to evaluate the Grocery Purchase Quality Index-2016 (GPQI-2016) as a tool for assessing grocery food purchase quality by using the Healthy Eating Index-2015 (HEI-2015) as the reference standard. DesignIn 2012, the USDA Economic Research Service conducted the National Household Food Acquisition and Purchase Survey. Members of participating households recorded all foods acquired for a week. Foods purchased at stores were mapped to the 29 food categories used in USDA Food Plans, expenditure shares were estimated, and GPQI-2016 scores were calculated. USDA food codes, provided in the survey database, were used to calculate the HEI-2015. Participants/settingAll households in the 48 coterminous states were eligible for the survey. The analytic sample size was 4,276 households. Main outcome measuresGPQI-2016 and HEI-2015 scores were compared. Statistical analyses performedCorrelation of scores was assessed using Spearman’s correlation coefficient. Linear regression models with fixed effects were used to determine differences among various subgroups of households. ResultsThe correlation coefficient for the total GPQI-2016 score and the total HEI-2015 score was 0.70. For the component scores, the strongest correlations were for Total and Whole Fruit (0.89 to 0.90); the weakest were for Dairy (0.67), Refined Grains (0.66), and Sweets and Sodas/Added Sugars (0.65) (all, P<0.01). Both the GPQI-2016 and HEI-2015 were significantly different among subgroups in expected directions. ConclusionsOverall, the GPQI-2016, estimated from a national survey of households, performed similarly to the HEI-2015. The tool has potential for evaluating nutrition education programs and retail-oriented interventions when the nutrient content and gram weights of foods purchased are not available.

Developing Customer Service Standards

AbstractEnsuring effective customer service requires targeted efforts in a number of areas, one of which is to develop service standards for each market segment. Differentiating customer service is achieved by adopting different standards according to the following criteria: availability of assortment varieties and quantities in percentage of orders placed; actually delivered quantities and assortment varieties in percent of the ordered ones; time (cycle) to execute orders in hours or days, and more. The development of service standards uses the results of its analyzes and assessments. Standards relating to customer service should be developed in the following areas: responsibilities of management; quality control system; supplier's obligations; design management; document management; purchase quality; product identification; management of the processes of providing services; customer service quality assessment; management of control, measuring and implementation equipment; corrective actions applied in the case of established discrepancies in the provided services; loading, unloading, storing, packaging, delivery and storage of the product; customer interaction; control over data related to service quality; internal audits related to service quality; personnel training; statistical methods. This paper explores the need and capability to develop customer service standards and provides an algorithm for developing standards for employee behaviour toward customers

Experiential Purchase Quality

Experiential purchases, such as movies, theme parks, and vacations, represent a unique, and exceedingly popular, type of marketing behavior. Despite the increasing popularity of purchased experiences, the question of what makes one experiential purchase superior to another remains elusive. Using a multimethod, grounded theory approach, the authors perform two qualitative studies that reveal high-quality experiential purchases are composed of five dimensions: uniqueness, fun, escapism, servicescape quality, and social congruence. Next, an empirical model of experiential purchase quality (EPQ) and its outcome variables is tested in two different settings. The results find support for the EPQ conceptualization and uncover that a high-quality experiential purchase can positively influence braggart word of mouth, nostalgia, and self-connectedness to the experience while also lowering price consciousness perceptions to repeat the experience. A comparison of short and long experiences found that customers put a heavier weighting on concepts such as escapism and social congruence in shorter experiences where longer experiences had a heavier emphasis on the servicescape and perceptions of fun. From a managerial perspective, our results highlight that a one-size-fits all approach in experiential management is problematic. Managers need to understand that customers have different evaluative criteria depending on the length of an experiential purchase.

Customer Service Standards

Ensuring effective customer service requires targeted efforts in a number of areas, one of which is to develop service standards for each market segment. Differentiating customer service is achieved by adopting different standards according to the following criteria: availability of assortment varieties and quantities in percentage of orders placed; actually delivered quantities and assortment varieties in percent of the ordered ones; time (cycle) to execute orders in hours or days, and more. The development of service standards uses the results of its analyzes and assessments. Standards relating to customer service should be developed in the following areas: responsibilities of management; quality control system; supplier's obligations; design management; document management; purchase quality; product identification; management of the processes of providing services; customer service quality assessment; management of control, measuring and implementation equipment; corrective actions applied in the case of established discrepancies in the provided services; loading, unloading, storing, packaging, delivery and storage of the product; customer interaction; control over data related to service quality; internal audits related to service quality; personnel training; statistical methods. The development and implementation of standards requires the organization to accurately determine customer service types, the cost of providing alternative services, and measures for measuring and controlling the services provided. At the core of the developed and implemented standards is the development and establishment of the customer service policy, which should start with a consumer demand analysis. The definition of customer service level should allow for quantitative measurement because the vague and quantifiable policy does not provide opportunities for evaluation and control of the activities and expenses of customer service. When developing service standards, it is appropriate to apply an algorithm that focuses primarily on standards related to employee behavior towards customers. This paper explores the need and capability to develop customer service standards and provides an algorithm for developing standards for employee behavior toward customers.

The Grocery Purchase Quality Index-2016: An innovative approach to assessing grocery food purchases

The study developed and validated a system for scoring the quality of household grocery purchases, the Grocery Purchase Quality Index-2016 (GPQI-2016). A grocery sales data set (2012–13) without individual household shopper attributes was provided by a national grocery chain, and a sample of 4000 households in each of four geographic locations was drawn. The 1887 categories, known as “subcommodities,” in the database were classified into the 29 food categories of the US Department of Agriculture’s Food Plan market baskets. A standardized expenditure share for each category was calculated. Quality of food purchases was evaluated by comparing the observed to the standardized USDA expenditure share for each category and then grouping the categories into 11 components, based on the Healthy Eating Index-2010. Processed meat expenditures were also assessed. Households that never purchased tobacco (n=12,460) had higher (6%) median total quality scores (31.3 of a possible 75 points) than those who did purchase tobacco (n=3540, median score 26.6, p<0.01), as well as higher scores for each of the 11 components (p<0.01). Tobacco users typically have poorer diets than non-users; therefore, construct validity of the GPQI-2016 in assessing grocery food purchases was established.

Grocery Purchase Quality Index‐2016 Scores Are Moderately Correlated with Healthy Eating Index‐2010 Scores in the Food Acquisition and Purchase Survey, 2012–13

ObjectiveThis study evaluates the Grocery Purchase Quality Index‐2016 (GPQI‐2016), a new tool developed at the University of Utah for assessing household grocery food purchase quality. We used the Healthy Eating Index‐2010 (HEI‐2010), a well‐validated assessment method, as the reference standard. Instead of using amounts of foods or nutrients, the GPQI‐2016 is based on the expenditure shares for the 29 food categories found in the USDA Food Plans. It includes the eight food‐based adequacy components (Total Vegetables, Greens and Beans, Total Fruit, Whole Fruit, Whole Grains, Dairy, Total Protein Foods, and Seafood and Plant Proteins) and one food‐based moderation component of the HEI‐2010 (Refined Grains), plus additional moderation components for Added Sugars and Processed Meats. Components of the HEI‐2010 not included in the GPQI‐2016 are Fatty Acids, Sodium, and Empty Calories.MethodsIn 2012–13 the USDA Economic Research Service (USDA‐ERS) conducted the National Household Food Acquisition and Purchase Survey (FoodAPS). Household members recorded all foods purchased for a week‐‐both foods purchased at stores for at‐home use (“foods at home” (FAH)) and foods obtained and eaten away from home. FoodAPS includes information on prices paid for each food item in a purchasing event or transaction. We mapped the USDA‐ERS food group classifications, provided in the survey database, to the 29 food categories used in USDA Food Plan market baskets so that the expenditure shares could be estimated. The 8‐digit USDA food codes, provided in the survey database, were used to calculate the HEI‐2010. After scoring FAH purchases by participating households (n=4,134), using each assessment method, the weighted Pearson's r coefficient was used to compare the total GPQI‐2016 scores with the total HEI‐2010 scores. The correlations for the nine food‐based components used in both indexes were also estimated.ResultsThe weighted Pearson's correlation coefficient for the Total HEI‐2010 and the total GPQI‐2016 scores was 0.61 (p &lt; 0.01). The strength of the correlations between the HEI‐2010 and the GPQI‐2016 components varied (p &lt; 0.01 for all). The strongest associations were found for three of the adequacy components, Whole Grains (0.77) and Total and Whole Fruit (both 0.75); while for the others, associations were more moderate, ranging from 0.42 for Total Protein Foods to 0.58 for Total Vegetables. For Refined Grains, a moderation component, the correlation was 0.45.ConclusionsOverall, the association of the GPQI‐2016 and the HEI‐2010 was moderate, and it varied by component. The process used to map the FoodAPS data to the USDA Food Plan categories could be refined by mapping at the food item level rather than at the food group level and may result in higher correlations in future versions of the GPQI.Support or Funding InformationNIH grant T15‐LM007124, the Western Regional Nutrition Education and Obesity Prevention Center of Excellence (USDA‐NIFA‐OP‐004574), and the USDA National Institute of Food and Agriculture (2015‐09151)

Determinants of online purchase intention: a study of Emirati consumers

In the online environment, lack of interaction among the buyers and the sellers further establishes that it is essential to understand the antecedents of online purchase intention. This study theorises a conceptual model to establish the relationship of online purchase intention with the antecedents of online purchase intention in the United Arab Emirates (UAE) market. The outcomes of the study are helpful to the online marketers to design a better marketing strategy to influence the online purchase intention of the online customers. The selected constructs borrowed from the literature have been used for data collection from Emirati consumers. Survey data from 478 Emirati consumers have been used to validate the conceptual model by using the factor analysis and multiple regression analysis. The study validates a conceptual model to establish the relationship among the antecedents of online purchase intention with the online purchase intention. The study has found out that brand orientation, prior online purchase experience, impulse purchase orientation, quality orientation and online trust have a significant influence on the online purchase intention. However, brand orientation does not have a significant influence on the online purchase intention.