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Online shopping around the world is growing exponentially, especially during the COVID-19 pandemic. This study aims to examine how an online customer's purchasing experience influences his/her buying intention and willingness to believe in fraud news, as well as the ripple impact of satisfaction and trust, with gender as a moderator in an emerging economy during COVID-19.

Based on the underpinning of the stimulus-organism-behavior-consequence (SOBC) theory, the research model was developed, and collected data from 259 respondents using convenience samples technique. Next, the data were analyzed using partial least squares-based structural equation modeling (PLS-SEM), SPSS (Statistical Package for the Social Sciences) and Hayes Process Macro.

The study results confirmed that the online shopping experience (OSE) has positive impact on customers' satisfaction (CS), purchase intention (PI) and customer trust (CT); CS has positive effects on trust toward online shopping and their future product PI; future product PI significantly affects customers' propensity to believe and act on fraud news (PBAFN). The finding also states that gender moderates the relationships of CS to PI, OSE to PI and PI to PBAFN, but doesn't moderate the CT to PI relationship.

The study findings will assist policymakers and online vendors to win customers' hearts and minds' through confirming satisfaction, trust and a negative attitude toward fake news, which will lead to customer loyalty and the sustainable development of the industry. Finally, the limitations and future research directions are discussed.

This paper aims to determine the factors that influence the consumer’s online shopping intention in the current pandemic context (COVID-19). For this purpose, a conceptual model has been developed by introducing the constructs “attitude,” “perceived utility,” “intention” as well as the variable “perceived risk of contagion.”

After collecting data from the questionnaire diffused in Moroccan e-commerce websites, this study used various statistical analyses with the multiple regression model on the SPSS statistical software to confirm or refute the research hypotheses.

The results indicate that attitude and perceived utility positively affect online shopping intention. However, the variable “perceived risk of contagion” has a weak effect on such intention, which can be explained by the period in which the survey was started (a few months after the confinement).

The scientific contribution of this study lies in the insertion of a new factor that will be called “perceived risk of contagion” in the research model. This factor has been inspired by the perceived risk theory of Bauer (1960). Furthermore, all studies dealing with this topic have been carried out in developed countries, such as France, Great Britain, Germany and the USA. For this reason, the researcher believe that it is more appropriate to study the intention to buy online during the COVID-19 pandemic in one of the developing countries, such as Morocco. This is based on the fact that to develop theories, it is necessary to examine a given problem in several countries. The context plays a determining role in such situations.

Within critical-infrastructure industries, bow-tie analysis is an established way of eliciting requirements for safety and reliability concerns. Because of the ever-increasing digitalisation and coupling between the cyber and physical world, security has become an additional concern in these industries. The purpose of this paper is to evaluate how well bow-tie analysis performs in the context of security, and the study’s hypothesis is that the bow-tie notation has a suitable expressiveness for security and safety.

This study uses a formal, controlled quasi-experiment on two sample populations – security experts and security graduate students – working on the same case. As a basis for comparison, the authors used a similar experiment with misuse case analysis, a well-known technique for graphical security modelling.

The results show that the collective group of graduate students, inexperienced in security modelling, perform similarly as security experts in a well-defined scope and familiar target system/situation. The students showed great creativity, covering most of the same threats and consequences as the experts identified and discovering additional ones. One notable difference was that these naïve professionals tend to focus on preventive barriers, leading to requirements for risk mitigation or avoidance, while experienced professionals seem to balance this more with reactive barriers and requirements for incident management.

Our results are useful in areas where we need to evaluate safety and security concerns together, especially for domains that have experience in health, safety and environmental hazards, but now need to expand this with cybersecurity as well.

The food industry is continuously developing its online services called food delivery applications (FDAs). This study aims to evaluate FDA's importance–performance and identify strategies to maximize its potential gains from a business partner's perspective.

Data are collected from 208 FDA partners in Indonesia. Importance–performance analysis (IPA) is applied to evaluate the FDA feature and extended the theory of potential gain in customer value (PGCV) to achieve potential gains from FDA business partners.

This study provides a clear and measurable direction for future research to develop FDA performance. Owning customer data, revenue sharing and competitive advantage are the most potential gains from joining the FDA from the business partner perspective.

The respondents are restaurants from the micro, small, and medium enterprises levels. Further research should involve middle to upper level restaurants to discover all business partners' perceptions. This will be very helpful for FDA providers interested in improving the best performance for all their partners.

FDA providers must focus on improving and maintaining the features of owning customer data, revenue sharing, competitive advantage, stable terms and conditions, customer interface, building customer loyalty, online presence, user credit rating, promotion and offers, delivery service and sales enhancement to increase consumer satisfaction and meet the expectations desired by business partners.

This research provides a meaningful theoretical foundation for future work. It extends the theory of PGCV using the value of a partner perspective as a substitute for customer value; hence, the authors call it a potential gain in partner value.

This paper aims to understand the most efficient hotel system and why efficiency varies across years and between the two differing types of hotel businesses in Turkey.

A data envelopment analysis (DEA) analysis was used to characterise the efficiency of all-inclusive (AI) and bed and breakfast (B&B) hotel businesses with one output (total revenue) and three inputs (labour, food and capital costs). The Malmquist approach is then used to discern changes in total efficiency (TTE) and intertemporal shifts in the efficiency frontier (technological change (Tch)).

The results reveal that the AI hotel operates at 100% efficiency in the summer and year-round. The B&B hotel business operates at 89.6% with variable constant returns to scale during the summer and with 100% efficiency. The results of the Malmquist approach indicate that the total factor productivity grew in the years 2015, 2016, 2018 and 2019, while the other years were marked by inefficiency. Such increases were due to technical efficiency change (TEch) and Tch, which means that managerial and allocative efficiency (AE) were barely achieved. Slight differences were noted in the two time periods (all year and summer), suggesting that the scale of hotel businesses is prepared to operate all year round, and this calls for strategies to mitigate seasonality.

As to avenues for future research, the limitations of this study are threefold. First, the hotel businesses are not parallel in terms of the duration of their service offerings. Future research may consider including an AI hotel business that is in operation for the whole year. Second, businesses in Turkey are sceptical about sharing their data as it is considered confidential. However, to better generalise the results and encourage hoteliers to consider the positive outcomes of such analysis, the number of observations could be increased by considering more hotel businesses in both categories. Third, a mixture of data representing businesses operating in various countries may reflect if the efficiency scores vary internationally.

Overall, AI hotel businesses are more attractive but less efficient than B&B. Furthermore, the external crisis impacts the efficiency of hotel businesses meaning that hotel managers could keep on exploring AI, perhaps educating their hosts not to waste or not offer huge quantities. Hotel managers may also need to enlarge their seasonal activities to ensure more efficiency.

Despite the intentions of AI hotel businesses to increase their profitability with a lower level of service quality, this study shows that the AI hotel business is very attractive but not so efficient due to the higher propensity of guests to consume food and beverages in excess that compromises the definition of efficiency as zero waste. AI is very attractive for family groups or those seeking the pleasure of relaxation at seaside resorts and is also very popular in Turkey. On the other hand, the B&B hotel business is more efficient but less attractive.

The contributions of this paper are threefold. First, the authors analysed the efficiency and inefficiency of hotel businesses within nine years of operations. During this period, Turkey experienced first a tourism boom (2011–2014) followed by stagnation and subsequently a sharp decline due to political instability resulting in an (in)direct impact on tourism (2015–2019). Second, the authors compared the efficiency and inefficiency of AI and B&B hotel businesses. Third, the authors examined the effects of hotel management factors to ensure efficiency.

Whether a human body has a healthy carrying capacity is calculated by body mass index (BMI). The BMI is found by dividing body weight in kilograms by the square of body length. If the person's body weight is more than the heaviness that the body can carry healthily, it is called obesity. Destinations have a specific area, just like a human body. Therefore, any destination whose carrying capacity is exceeded can be called an “obese destination”. This study's primary purpose is to reveal the importance of destination carrying capacity through the concept of obesity.

Content analysis, one of the qualitative research methods, was employed, and graffiti reflecting the feelings of the local people toward tourists were used as data. Graffiti was considered as a social carrying capacity indicator to identify obese destination symptoms. Fifty graffiti obtained from search engines about destinations with obesity problems were analyzed.

The study's findings reveal that anti-tourist graffiti indicates obese destination symptoms. Furthermore, when the content analysis of graffiti is examined, it is seen that the obese destination's local people have intense anger toward tourists. This is a clear manifestation of the destination's health deterioration.

This study, in which the concept of obese destination is used for the first time, suggests that destinations' health may worsen just like people. If destinations with over-tourism are called obese, a more expansive awareness will be created about the destinations' problems. The study suggests that nonecolabel can be used as a mandatory diet tool for obese destinations. Anti-tourist graffiti has been addressed as an obese destination symptom.

Chinese consumers’ cross-border internet shopping, so called “haitao” is an emerging popular trend in China. Haitao can be understood as service innovation process because it creates new market spaces and provides differentiated values for Chinese customers.

This study aims to explore the service innovation strategies and success factors of haitao business in the Chinese market. The authors selected two successful haitao sites of Amazon.cn and Gmarket.co.kr, as representatives of a global player and a niche player, and conducted a comparative case study to analyze their service innovation strategies and key success factors.

This comparative case analysis based on value chain framework revealed some common success factors such as trust, advanced system and alliances as well as their service innovation efforts. Amazon has advantages such as efficient logistics system and global sourcing, whereas Gmarket has advantages such as product category, sales promotions, and payment system.

This study provides some implications for managers with localization, alliances and platform strategies.

This study aims to, first, propose a valid and reliable scale to document the COVID-19 Pandemic Shopping Experience (CPSE) and, second, determine the impact of its variables on the postpurchase shopping experience (PPSE).

For scale development, published studies were scanned and the variables were shortlisted. These shortlisted variables were validated by 52 faculties from four universities in Saudi Arabia. Data were collected from 318 respondents to purify the CPSE Scale. In Study 2, a path analysis was performed on a sample of 354 respondents to determine the individual impact of each variable on PPSE.

A total of 14 items were found to be aligned under four variables, social distance (SD), shop hygiene, operational time and entertainment venues. SD was found to have the greatest influence on PPSE, followed by operational time and shop hygiene.

This research has important implications for retailers to initiate changes in store layout so that they can implement social distancing by physically marking stickers on the floors and by placing barricading on billing counters. Store hygiene can be ensured by making sanitizers and hand gloves available at the entry points, periodically cleaning the floor and sanitizing the premises. Rationing the operating time proved to be an effective tool to minimize the exposure time, thereby limiting consumers' time inside the store.

To the best of the authors’ knowledge, this is the first study to propose a full-scale measure of the customer shopping experience (SE) during a pandemic. This scale can be generalized to measure SE in similar situations.

Consumers are increasingly combining distribution channels, thus displaying so-called omni-channel behavior, both to complete a given purchase and between purchases. The authors make a distinction between omni-channel customers, who make use of distribution services in both channels and omni-channel users, who make partial use of the distribution services of one channel to support purchases in another. This paper aims to identify the omni-channel behavior among the customers of a global fast fashion retailer dealing in a wide range of apparel and clothing accessories.

Using a multinomial logit model, the authors perform a customer segmentation based on observed omni-channel behavior, considering the explanatory roles of demographics, distribution service features and customer service policies across the different retail channels.

The authors observe that the key retail channel features for explaining omni-channel customer behavior are product accessibility, both in store and online; the assurance that goods purchased online will satisfy the customer’s needs and expectations; and the option to return goods found unsatisfactory.

The results clearly show that the nature of the visits and purchases made by customers is determined by various components of the companýs customer service policy, which can, therefore, be used to guide the retailer’s segmentation strategy.

Future lines of research should explore the economic implications of this customer segmentation. The price perception data emerging from our findings suggest a greater sensitivity to prices in the mono-channel segment, which might be worth exploring in future research.

Future lines of research should explore the economic implications of this customer segmentation. The price perception data emerging from our findings suggest a greater sensitivity to prices in the mono-channel segment which might be worth exploring in future research.

Los consumidores combinan canales de distribución en el denominado comportamiento omni-canal cada vez en mayor medida, tanto para completar una misma compra como entre distintas compras. Distinguimos entre clientes omni-canal, que hacen uso de los servicios de distribución de ambos canales, y usuarios omni-canal, que hacen solo un uso parcial de los servicios de distribución de un canal para apoyar las compras en el otro canal. En este trabajo identificamos este comportamiento omni-canal entre los clientes de una empresa global del sector de la moda que vende un amplio rango de productos de ropa y complementos.

Mediante un modelo logit multinomial, realizamos una segmentación de los clientes en base a su comportamiento omnicanal. En esta segmentación, consideramos el papel explicativo, no solo de las características de los individuos, sino también el de los servicios de distribución y las políticas en cada canal.

Obtenemos cómo el acceso al producto, tanto en el establecimiento como a la página web, la garantía de que el producto comprado online tendrá las características esperadas y las facilidades para devolver el producto adquirido online si no cumple las expectativas, son rasgos clave de los canales que explican el comportamiento omnicanal de los clientes.

Nuestros resultados muestran claramente que diferentes aspectos de la oferta de servicios y de políticas de la empresa determinan las compras y las visitas y estos aspectos pueden ser utilizados para guiar la estrategia de segmentación del detallista.

En este trabajo contribuimos a la literatura sobre el marketing omnicanal presentando un modelo de segmentación, basado en los servicios de distribución ofertados por los minoristas, para las empresas que comercializan productos a través de distintos canales. Aportamos una distinción conceptual entre usuarios de un canal y compradores que tiene un amplio rango de aplicación.

Es necesario proseguir con las líneas futuras de investigación para investigar las implicaciones financieras de esta segmentación. La percepción de los precios que se detecta en nuestros resultados puede sugerir una sensibilidad mayor a los precios en el segmento mono-canal lo que puede ser una línea interesante a contrastar en investigaciones futuras.

Omni-canal, Moda rápida, Trabajo de investigación, Segmentación, Servicios de distribución, Comercio electrónico

Trabajo de investigación

This study investigates the factors influencing re-usage intention of online and mobile grocery shopping among young adult consumers in South Africa.

Data were collected from selected young adult participants using a stratified probability sampling strategy. Smart PLS was used to analyse the data.

The findings of the study indicate that perceived usefulness (PU), peer review (PR) and attitude (ATT) positively influence continuance intention (CI).

In line with the available literature, there are few prior post-adoption studies that delineate the influence of individual characteristics on digital commerce usage activities. There is high mobile penetration as a result of positive digital commerce and mobile application usage and adoption, creating the need to investigate and better understand the drivers behind, not just adoption and usage, but continued use of digital commerce platforms and applications. Since the sample size is relatively small, further future research studies can test the same model with bigger sample sizes to assess generalisability of the results in different locations.

This study adds to the current literature by concentrating on the extent to which systems and marketing elements influence young adult customers' intention to continue using online and mobile grocery shopping platforms in South Africa.

The study adds value from a theoretical standpoint, contributing to the antecedent factors of the technology acceptance model (TAM), theory of reasoned action (TRA) and stimulus-organism-response (S-O-R) model and giving marketing academics insights into what aspects drive re-use of online and mobile grocery shopping and on what should be the focus.