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This study addresses the impact of aesthetics and formality in Food Delivery Applications (FDAs) in evoking emotions, and how these influence the intention to reuse and compulsive usage, providing critical insights for designing responsible and effective marketing strategies.

A quantitative analysis of data collected from 1,029 FDA users was employed, using the PAD (Pleasure, Arousal, Dominance) theory to investigate how aesthetic design and formality affect emotions and consumer behaviour towards the applications.

The study reveals that aesthetic appeal and formality significantly impact emotions of dominance, arousal, and pleasure, which are decisive in users' decisions to continue using FDAs and in the manifestation of compulsive usage behaviours.

This study presents inherent limitations due to its cross-sectional design, which prevents offering a longitudinal perspective on the evolution of consumer behaviour regarding FDAs. The actual purchasing behaviour is not examined, but rather the suggested experiences. Future research could be enriched by considering cultural, social, and demographic factors, the influence of sustainability on the perception and use of FDAs, and the importance of specific sustainable practices. Adopting a longitudinal approach and utilising actual usage data would allow for a deeper and more nuanced understanding of consumer behaviour towards FDAs, taking into account both personal factors and functional attributes of FDAs along with their aesthetic appeal and emotional reactions.

The findings provide guidelines for FDA companies to optimise their interfaces to enhance user experience, foster loyalty, and prevent compulsive usage. They emphasise balancing aesthetics and functionality to induce more conscious and sustainable consumption behaviours.

This study highlights significant social implications stemming from the integration of aesthetic appeal and formality in Food Delivery Apps (FDAs) and their effect on consumer emotions, which in turn influences reuse intention and compulsive use. Amidst the COVID-19 pandemic, consumer behaviours have shifted towards increased electronic transactions and hedonic consumption as responses to stress, anxiety, and boredom, leading to a reevaluation of life experiences through technological means. The research underlines the critical role of emotions, particularly pleasure, dominance, and arousal, in promoting the intention to reuse FDAs, which has far-reaching implications for consumer engagement, compulsive usage patterns, and the need for responsible, sustainable consumption practices. It suggests a new avenue for businesses and policymakers to consider emotional impacts and consumer satisfaction in the design and regulation of FDAs, aiming to mitigate potential adverse effects of compulsive usage and to encourage sustainable, responsible consumption behaviours.

The research offers a novel perspective by exploring how aesthetic and emotional dimensions affect consumer loyalty and compulsivity. These areas are still to be examined in depth in the marketing literature. The findings enhance the theoretical and practical understanding of FDA marketing, demonstrating how design can influence consumer well-being and the sustainability of purchasing behaviour.

1. Novel use of PAD theory to analyse FDA’s aesthetic appeal and formality on user emotions.

2. FDA’s aesthetic appeal significantly influences reuse intentions and compulsive usage.

3. Emotions of pleasure, dominance, and arousal are directly linked to FDA reuse intention.

4. Pleasure and reuse intention influence the compulsive use of FDAs.

Novel use of PAD theory to analyse FDA’s aesthetic appeal and formality on user emotions.

FDA’s aesthetic appeal significantly influences reuse intentions and compulsive usage.

Emotions of pleasure, dominance, and arousal are directly linked to FDA reuse intention.

Pleasure and reuse intention influence the compulsive use of FDAs.

An AI concierge is a technologically advanced, intelligent and personalized assistant that is designated to an individual customer, proactively taking care of that customer’s needs throughout the service journey. This article envisions the idea of AI concierges and discusses how to leverage AI concierges in the customer journey.

This article takes a conceptual approach and draws insights from literature in service management, marketing, psychology, human-computer interaction and ethics.

This article delineates the fundamental forms of AI concierges: dialog interface (no embodiment), virtual avatar (embodiment in the virtual world), holographic projection (projection in the physical world) and tangible service robot (embodiment in the physical world). Key attributes of AI concierges are the ability to exhibit semantic understanding of auditory and visual inputs, maintain an emotional connection with the customer, demonstrate proactivity in refining the customer’s experience and ensure omnipresence through continuous availability in various forms to attend to service throughout the customer journey. Furthermore, the article explores the multifaceted roles that AI concierges can play across the pre-encounter, encounter and post-encounter stages of the customer journey and explores the opportunities and challenges associated with AI concierges.

This paper provides insights for professionals in hospitality, retail, travel, and healthcare on leveraging AI concierges to enhance the customer experience. By broadening AI concierge services, organizations can deliver personalized assistance and refined services across the entire customer journey.

This article is the first to introduce the concept of the AI concierge. It offers a novel perspective by defining AI concierges’ fundamental forms, key attributes and exploring their diverse roles in the customer journey. Additionally, it lays out a research agenda aimed at further advancing this domain.

Extending the elaboration likelihood model (ELM), this study investigates the impact of social media influencers (SMI) on consumer well-being (CW) as well as the influence of CW on purchase intention.

A between-subjects experiment (macro- vs mega-influencer) was conducted to assess the proposed hypotheses. A total of 190 consumers participated in the experiment, and SmartPLS 3.3 was used for multigroup analyses.

Overall, argument quality (AQ), source's credibility (SC) and influencer's kindness positively predict CW, and CW predicts purchase intention. It was also found that SC is more important when information comes from a mega-influencer, whilst kindness is essential for a macro-influencer.

The results of this study imply that CW should be an essential component of influencer marketing strategy. Marketing managers should hire credible and kind influencers who can produce quality arguments. Additionally, the selection of SMI (macro- vs mega-influencer) should be aligned with the marketing objective and type of persuasion required.

This is one of the early attempts to extend ELM by introducing influencer kindness as a peripheral cue. Moreover, the study offers novelty by examining the effects of influencer characteristics (AQ, SC and kindness) on CW and comparing these effects across macro- and mega-influencers.

藉著擴展詳儘可能性模型, 本研究擬探討網絡紅人對消費者福祉的影響, 以及消費者福祉對購買意圖的影響。

研究人員進行被試間實驗 (中網紅對大型網紅) , 以對提出的假設進行評價。190名消費者參與實驗, 研究人員使用SmartPLS 3.3 進行多群組分析。

總的來說, 論點品質、來源可信度和網紅的仁慈體貼, 均能積極預測消費者福祉, 而消費者福祉亦可預測購買意圖。研究人員亦發現, 若資訊是來自大型網紅的話, 來源可信度則更形重要, 而對中網紅來說, 仁慈體貼則是不可或缺的。

研究結果暗示, 消費者福祉應是網紅市場營銷戰略的基本要素。市場經理應僱用可靠、仁慈體貼、並能提出優質論點的網紅。而且, 網絡紅人 (中網紅對大型網紅) 的挑選, 必須與營銷目標和說服的種類互相協調。

本研究為早期的嘗試, 利用引進網絡紅人的仁慈體貼作為周邊線索, 來擴展詳儘可能性模型。另外, 本研究探討網絡紅人的特徵 (論點品質、來源可信度和仁慈體貼) 會如何影響消費者福祉; 研究人員亦跨中網紅和大型網紅, 對這些影響進行比較, 就此而言, 本研究提供了創新的研究意念。

The paper aims to examine the role played by property tax in influencing strategic decisions regarding marital separation and divorce in Italian municipalities.

The empirical analysis is conducted on a sample of 6,458 Italian municipalities by applying the ordinary least squares (OLS) and instrumental variables (IVs) approaches.

The estimation results show a small increase in marital separations and divorces as the difference between the municipal secondary and primary home tax rate increases. Specifically, an increase of 1‰ in the property tax rate differentials is accompanied by an increase of six marital separations and four divorces per 1,000 inhabitants.

The main limitation of the analysis is that the strategic behavior of the married couple is inferred from econometric analysis with data aggregated at the municipal level. To investigate this phenomenon more precisely, it would be useful to have individual data collected by surveys on strategic divorce decisions due to property tax incentives.

This study contributes to the scant existing literature on the tax incentives for strategic divorce. It is the first study to empirically investigate the effects of property tax on separation and divorce decisions by investigating the Italian context. In Italy, a property tax was introduced in 1993, encouraging “false” divorces by spouses with a second home since the tax on the secondary home was set at a rate higher than that on the primary residence. Moreover, there were no tax deductions and no additional tax breaks on the secondary home, while they were established on the primary one. Higher property taxes and the absence of tax breaks on the secondary home may have encouraged a strategic behavior whereby many married couples filed for false separation and divorce in order to recover part of property tax rebates.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

Posting and sharing about food on social media has surged in popularity amongst younger generations such as Millennials and Generation Z. This study aims to analyse and compare food-tourism sharing behaviour on social media across generations. First, this study specifically investigates the factors influencing the intention to share food experiences on social media; second, it examines the impact of sharing intention on actual behaviour and loyalty; and third, it determines whether Millennials and Generation Z differ in these relationships.

A survey was carried out of Millennial and Generation Z travellers who shared food experiences on social media. Structural equation modelling (SEM) and multi-group analysis were performed to examine the cause-and-effect relationship in both generations.

The findings reveal differences in motivation, satisfaction, sharing intention, sharing behaviour and loyalty between generations (Millennials and Generation Z).

This study contributes to the literature on the antecedents of food-sharing behaviour in online communities by indicating factors that influence the sharing of culinary experiences and brand or destination loyalty across generations. Suggestions for future research include exploring online food-sharing behaviour through cross-cultural comparisons in various regions.

As Millennials and Generation Z will expand their market share in the coming years, the findings of this study can help improve marketing strategies for culinary tourism and generate more intense food experiences for both generations.

The outcome of the research provides new insights to develop a conceptual model of food-sharing behaviour and tourism on social media by drawing comparisons across generations.

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.

Although improving customer experience (CX) has always been one of the top priorities of business process management (BPM), the evidence on the actual contribution made by traditional BPM to improving CX and customer experience management (CXM) is mixed. Recently, new and enhanced capability areas have been added to the traditional BPM frameworks, yet it is unclear which of them contribute to CXM. Moreover, it is not known which of them are necessary and which are sufficient conditions. The aim of this research is to shed light on the research gap concerning which BPM capabilities, especially new and enhanced ones, are relevant to CXM.

Quantitative data from 268 medium and large companies in 3 EU countries were analysed using hierarchical linear regression analysis and necessary condition analysis.

The results show that traditional BPM capabilities are a necessary condition for CXM, but with minor significance. Most highly significant necessary conditions and also most highly or medium significant sufficient conditions belong to the People or Culture area. Agile Process Improvement is the only new or enhanced BPM capability area in the Methods/IT area that is a necessary and also a sufficient condition for CXM maturity. Advanced Process Digitalisation was identified as neither a significant necessary nor a sufficient condition for CXM.

This research contributes to better understanding of the role played by BPM for CXM, where previous research provides mixed results.

Recognizing novel entrepreneurial opportunities arising from a crisis is of paramount importance for firms. Hence, understanding the pivotal factors that facilitate firms in this endeavor holds significant value. This study delves into such factors within a representative empirical context impacted by a crisis, drawing insights from existing literature on opportunity recognition during such tumultuous periods.

The authors conducted a qualitative inspection of 14 Italian firms during the COVID-19 pandemic crisis. The authors collected a rich body of multi-source qualitative data, including 34 interviews (with senior managers and entrepreneurs) and secondary data (press releases, videos, web interviews, newspapers, reports and academic articles) in two phases (March–August 2020 and September–December 2020).

The results suggest the existence of a process model of opportunity recognition during crises based on five entrepreneurial influencing factors (entrepreneurial knowledge, entrepreneurial alertness, entrepreneurial proclivity, entrepreneurial personality and entrepreneurial purpose).

Various scholars have highlighted that, in times of crises, it is not easy and indeed very challenging for entrepreneurs to identify novel entrepreneurial opportunities. However, recent research has shown that crises can also positively impact entrepreneurs and their capacity to identify new entrepreneurial opportunities. Given these findings, not much research has analyzed the process by which entrepreneurs identify novel entrepreneurial opportunities during crises. This study shows that some entrepreneurial influencing factors are very important to identify new entrepreneurial opportunities during crises.