Measuring consumers' level of satisfaction for online food shopping during COVID-19 in Italy using POSETs

Abstract

The pandemic COVID 19 has upset the economic, social, financial, and general behavioral systems. Global crisis has a large impact overall and related fallouts significantly affect existent structural paradigms in every country and region across the world. In particular, the spread of COVID-19 pandemic has led to having to rethink the way we produce and consume food. Within this global change, a rise in the number of consumers who purchase food products online in order to comply with the rules aimed at limiting the circulation of the virus should be emphasized. Consequently, probably causing a long-term positive effect on m-commerce. The purpose is to elaborate on the index of the satisfaction level of consumers of purchasing food online via food shopping channels, by using key factors that characterize the online spending behavior. The analysis was carried out by collection of data deriving from an anonymous online questionnaire administrated via social networks and emails, during the 'hot' months of the pandemic progression in Italy, which is March-May 2020. We analyse both dimensions of customer satisfaction (process and outcome), by means of two systems of indicators. We reduce their complexity using synthesis obtained with the Partially ordered set. Results highlight the differences between the two dimensions of customer satisfaction. Online shopping can surely contribute to reduction of food waste thanks to elimination of frenzied shopping routines at supermarkets and can open space to new fields of study. On the other hand, defining an index of the consumer's satisfaction can alter sales strategies of m-commerce managers and entrepreneurs.

Keywords: COVID-19 pandemic; Food online shopping; Index of consumers' satisfaction; Italy; Online spending behavior; Partially order set; Poset; Synthesis of statistical indicators.

Fig. 1

Hasse diagram of the system in Table 2.

Fig. 2

Indicators of customer satisfaction for online food shopping: percentage distribution of levels of satisfaction.

Fig. 3

ρ Spearman correlation coefficients: average rank (AVR Process dim.), severity function (SEV Process dim.) and identification function (IDN Process dim.) of process dimension; average rank (AVR Outcome dim.), severity function (SEV Outcome dim.) and identification function (IDN Outcome dim.) of outcome dimension.

Fig. 4

Process and outcome dimensions of customer satisfaction: cumulative frequencies distribution of identification and severity functions.

Fig. 5

Process dimension of customer satisfaction: Hasse diagram.

Fig. 6

Outcome dimension of customer satisfaction: Hasse diagram.