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This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The authors examine Cloud computing systems and their benefits and pitfalls, as well as the security priorities of consumers with these servers. It is essential for firms to have secure places to store information, as trust and transparency underlie a firm's reputation.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The study aims to analyse the structural relationships of authenticity, health concern and sustainable intelligence in the farm restaurant context. Different types of restaurants have been targeted to understand consumer behaviour; however, the behavioural intention of visitors dining at the farm restaurants was rarely explored.

With the backdrop of the theory of planned behaviour (TPB), this study highlights the understanding, particularly on personal values associated with the behavioural intention of consumers visiting the farm restaurant. Data were collected, circulating questionnaires onsite and online at a farm restaurant. Structural equation modelling was employed to analyse the data.

Study findings reveal that personal values such as authenticity, health concern and sustainable intelligence positively influence the mediating constructs of TPB towards behavioural intention to revisit the farm restaurant.

This research might be the first one, exclusively focused on understanding the behavioural intention of the consumers visiting the farm restaurant, based on their personal values. This study specifically enriches the farm restaurant literature from the academic perspective and offers insights to farm restaurant owners and managers about the priorities of the consumers visiting the farm restaurant.

To provide a dynamic view on accommodation choice behaviors during the pandemic, this study aims to examine the impact of recent trends on prospective travelers’ preferences for hotels and Airbnb.

The paper adopts a mixed methods approach that incorporates three independent studies (experimental analysis, online search pattern analysis and an econometric event study) to understand customer decision-making behaviors.

The findings indicate that travelers prefer Airbnb entire flats/apartments to hotels when the pandemic is trending upward. This result externally validates travelers’ preference toward Airbnb during periods of high risk. Interestingly, when the trends go downward, however, the same behavioral pattern was not identified.

This study provides important empirical insights into how the evolution of health crises influence customer decision-making for hotels and Airbnb. Future research needs to consider the role of socio-demographic factors in accommodation selection behaviors and examine how travelers react to cleanliness levels between Airbnb and hotels.

As one of initial studies that empirically examine Airbnb customers’ decision-making behaviors in the context of the COVID-19 pandemic’s trends, this study provides a dynamic view on how the evolution of the pandemic influences accommodation choice behaviors.

The increased usage of smartphones has made mobile payment services (MPS) popular among millennials, but it is uncertain if this shift in behavior is temporary due to situational factors like the pandemic or a long-term trend due to technological advances. This study uses the diffusion of innovation (DOI) literature to assess an integrated model including smartphone addiction, technology-related and consumer-related factors that influence consumers' intention to use MPS. It also explores the interplay of situational variables and smartphone addiction in shaping this relationship.

The authors base the conceptual model on the theory of rational addiction and the theory of optimal flow. This model is then empirically validated through data collected from seven hundred users of MPS in India. Research hypotheses are tested using structural equation modeling and multi-group analysis.

The study finds that smartphone addiction has a positive impact on millennials' perceived advantages, compatibility, trialability and observability of MPS but does not significantly affect their perceived complexity or risk. The results also suggest that the relationship between smartphone addiction and MPS is moderated by situational factors. In low-priority situations, smartphone addiction strengthens millennials' perceptions and intentions to use MPS, while in high-priority situations, situational factors overshadow the impact of smartphone addiction.

The findings of the study enable organizations to capitalize on smartphone addiction-driven MPS adoption behavior to sustain long-term usage behavior by appropriately understanding the context/situation which drives MPS adoption.

This research delineates the interdependencies between e-service quality (e-SQ), product quality (PQ) and food biosafety measures (FBM) in shaping consumer satisfaction and loyalty within the online food delivery services (OFDS) landscape. Anchored by the technology acceptance model (TAM) and the theory of planned behavior (TPB), the study integrates these frameworks to examine how perceived service efficiency, reliability, product appeal and biosafety protocols contribute to overall consumer trust and repurchase intentions.

Surveys were conducted on several 100 online food delivery app users, ages 20 to 64, in major cities in Colombia, which provided data for structural equation modeling analysis.

The analysis revealed that reliable, responsive service and appealing food presentation significantly influence consumer perceptions of behind-the-scenes safety protocols during delivery. Strict standards around mitigating contamination risks and verifiable handling at each point further engender trust in the platform and intentions to repurchase among users. The data cement proper food security as pivotal for customer retention.

Quantitatively confirming biosafety’s rising centrality provides an impetus for platforms to integrate and promote integrity, safety and traceability protection as a competitive differentiator.

The study’s originality lies in its comprehensive exploration of the OFDS quality attributes and their direct impact on consumer loyalty. Besides, it offers valuable insights for both academic and practical implications in enhancing service delivery and marketing strategies.

This exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches explore users' behavior and attitudes toward the priorities of mobile app attributes and preferences, identifying correlations between attributes and aggregating individual attributes into groups.

Online convenience sampling and snowball sampling resulted in 417 valid responses. The numerical data are analyzed using the relative to an identified distribution (RIDIT) scoring system and gray relational analysis (GRA), and qualitative responses are investigated using text-mining techniques.

This study finds enhanced nuances of user preferences and provides data-driven insights that might help app developers and marketers create a distinct app that will add value to consumers. The latent semantic analysis indicates relationship structure among the attributes, and text-based cluster analysis determines the subsets of attributes that represent the unique functions of the mobile app.

This study reveals the essential components of mobile apps, paying particular attention to the consumer value component, which boosts user approval and encourages prolonged use. Overall, the results demonstrate that developers must concentrate on its functional, technical and esthetic features to make an app more exciting and practical for potential users.

Most scholarly research on apps has focused on their technological merits, aesthetics and usability from the user's perspective. A post-adoption multi-attribute app analysis using both structured and unstructured data is conducted in this study.

This paper aims to examine the online apparel shopping behaviour of Generation Y (Gen Y) in an unprecedented digital dissemination era.

For this purpose, a “mixed-method approach” was used with an explanatory sequential research design. Logistic regression was conducted to identify the role of various contemporary elements of shopping motives. Fifteen semi-structured interviews were conducted to explain quantitative outputs.

It finds that Gen Y consumers demonstrate “fashion-hunting”, “variety-seeking”, “status/recognition-seeking” and “deal-hunting” behaviours in online apparel shopping. “Haptic impressions” gained via hands and other “socio-psychological benefits” trigger their apparel shopping behaviour. They make better and more informed purchase decisions based on prior online research and user-generated content shared by friends/relatives on social media portraying the true characteristics of “digital natives”. They do not trust online retailers for premium apparel shopping due to associated “product risk” and lack of transparency in their “exchange/return/refund policy”. Finally, they are increasingly inspired to have an “integrated online and offline shopping experience”.

Online retailers can use the findings of this study to develop more effective marketing strategies to serve Gen Y consumers.

The study measured actual behaviours on a holistic gamut of shopping motives consisting of utilitarian, hedonic, physical product-specific (apparel) and emerging elements of shopping motives in the technology-enabled era of shopping exclusively. Therefore, the results of the study offer significant, realistic and useful theoretical contributions to the existing literature on the subject matter along with valuable inputs to practitioners alike.

This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’ person-goods matching process and how the platform firm’s similar strategies moderate the effects of TPSs’ strategies.

Using data collected from the top ten TPSs from a Chinese e-commerce platform, the fixed effect model is used to validate the conceptual model and hypotheses.

The study results show that both market detection strategy and matching optimization strategy can help large TPSs improve their sales performance. Moreover, the similar market detection strategy applied by the platform firm weakens the effect of large TPSs’ customer acquisition strategies, while the similar matching optimization strategy applied by the platform firm strengthens the effect of large TPSs’ customer acquisition strategies.

This study provides firsthand evidence on the performance of large TPSs’ and the platform firm’s strategies. It demonstrates the effectiveness of large TPSs’ market detection strategy and matching optimization strategy, which can be adopted to meet consumers’ search and evaluation motivations in their person-goods matching process respectively. Moreover, it identifies the role of platform firms by showing the moderating effect of similar strategies adopted by the platform firm on the effect of large TPSs’ customer acquisition strategies.

This study explores reasons for and against secondhand luxury (SHL) fashion adoption among young consumers in an emerging nation, India. As a trend, SHL has witnessed tremendous growth in the past few years, but scholarly interest remains scant.

Drawing from an interpretivist paradigm, this study uses an exploratory qualitative approach with 26 semi-structured interviews with SHL buyers, analyzed using NVivo software.

The findings shed significant light on value drivers and find support for status value, uniqueness value, quality value and monetary value, while adding the role of emotional value in reasons for SHL adoption. The results reveal an interesting trait of Indian consumers: price, fashion and celebrity association outweigh sustainability concerns, where an attitude–behavior gap is observed. Also, the findings add depth to risk perceptions as a major reason against SHL adoption.

While most existing studies have only focused on the motivational drivers, this study offers in-depth insights into the growing SHL literature by drawing attention to the enablers and equally important inhibitors by applying the novel Behavioral Reasoning Theory. It also intends to enhance practitioner knowledge in understanding a culturally diverse market and developing strategies relevant to a new set of consumers. The study calls for SHL retailers to sensitize young consumers in India about the sustainability aspect of SHL consumption, which is currently less appreciated.

This paper aims to examine the factors that influence bank customers’ acceptance towards FinTech using the unified theory of acceptance and use of technology (UTAUT) model.

A survey was carried out, and a judgemental sampling method was used. Moreover, over 200 responses were gathered from individuals that were bank account holders. Besides, the literature on the factors that influence an individual acceptance towards FinTech using the UTAUT model was also reviewed as an effort to contribute towards the factors that are significant in predicting the acceptance of FinTech services.

The results of the study revealed that performance expectancy and effort expectancy are the main factors in determining the acceptance of FinTech services. Moreover, consumer innovativeness plays an important role in the acceptance of FinTech by bank users. In contrast, social influence and facilitating conditions were not the determinants of FinTech acceptance in Pakistan.

This study not only contributed to the theoretical extensions but also to practical implications, which would benefit the community of FinTech service providers in Pakistan.

The limitations of this study were two but are not limited to, firstly, the respondents which were taken among bank customers in Pakistan, confining its contribution to the narrowed perspective of Pakistan. Besides, this study also considers its contributions towards the use of the UTAUT in which the factors examined were specific, which may elucidate that the generalization of the findings only includes FinTech, where the UTAUT comes into play. This study is an eye-opener for the merging perspective of both the UTAUT and FinTech.

UTAUT is extended in the context of FinTech. Consumer innovativeness is incorporated in the context of the UTAUT model. Consumer innovativeness is yet to be tested and for that this study is a useful reference for academicians, policymakers and future researchers.