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Academic literature calls for research on the impact of psychological states derived from mental illness on detrimental consumer behaviour. The purpose of this study is to assess the impact of anxiety on the consumer’s buying processes (compulsive and impulsive) and emotional regulation.

To carry out the statistical analysis, the data were obtained through an online survey (n = 726) of supermarket consumers. The treatment of the data was using partial least squares structural equation modelling (PLS-SEM).

The results obtained show that anxiety influences the generation of harmful behaviour, as it has a positive impact on compulsive and impulsive buying. In addition, compulsive and impulsive buying generate higher levels of consumers’ emotional regulation.

This study contributes to the management of anxiety as a priority element to reduce harmful behaviour. Therefore, it provides useful information for marketing managers and professionals in psychological and healthy consumer processes.

學術文獻不斷呼籲研究人員和學者去探討來自精神病的心理狀態如何產生有害的消費者行為。本研究擬評定焦慮對消費者購買流程 (強迫性購物和衝動購物) 和情緒調節所產生的影響。

為能進行統計分析,研究人員透過超級市場消費者的在線調查 (n = 726) 取得數據,繼而以結構方程 (PLS-SEM) 處理數據。

研究結果顯示,焦慮會導致有害行為的產生,這是因為焦慮對強迫性購物和衝動購物均產生積極的影響; 而且,強迫性購物和衝動購物會產生較高水平的消費者情緒調節。

本研究的貢獻在於把焦慮視為減少有害行為的優先元素而予以管理; 因此,本研究為市場經理以及於心理上的和健康的消費者進程的專業人員提供了有用的資料。

Buying directly from farmers online has become increasingly popular in recent years. This study aims to investigate the effect of the interaction between various consumption values that drive consumers to buy directly from farmers online. The proposed conceptual framework suggests that consumers who buy online directly from farmers are driven by an interaction of weighted individualistic consumption value (i.e. an integration of values such as saving money, getting quality and fresh produce) and collectivistic values (pro-environmental behaviour and ethnocentric perception).

Data were collected using a representative sample of 576 consumers via an online access panel and analysed using AMOS SEM.

A weighted individualistic consumption value affects consumer attitudes and, consequently, consumers' intention to buy agri-food products directly from farmers. Nonetheless, individualistic consumption value is more effective in enhancing attitudes among consumers with high pro-environmental behaviour. Moreover, ethnocentric perception lowers the effect of individualistic consumption value on attitudes and enhances the positive effect of attitudes on buying intention.

This study contributes to the literature on consumer online behaviour when buying food products directly from farmers. Its originality lies in the effect of interacting individualistic and collectivistic consumption values to explain consumer motivation for this behaviour.

Buying online has become a widespread and common activity for consumers, and, for many organizations, e-commerce has become a very profitable alternative to sell their products and services, also allowing them to leverage their strategy in new geographical markets immediately. Although the literature on the subject is comprehensive, there is a gap in identifying the holistic constructs that are the determinants of consumers' choice of an online store. This research resorts to an exploratory study, based on a nonsystematic literature review, seeking to identify these constructs. The results obtained allowed us to identify the following constructs: consumer behavior, customer experience, web content, catalog, terms and conditions, customer support, perceived value, trust, security and privacy, satisfaction, and loyalty. Customer experience, satisfaction, and loyalty constructs stand out from a strategic perspective.

Understanding the effect of assortment composition on attentional levels is an essential topic for academic researchers and practitioners. This work has important implications when analyzing the influence of shopping frame time and search effort on the relationship between the reaction to assortment composition and visual attention to stock-keeping units (SKUs) pricing.

Two experimental studies through gauze behavior analysis technology (using eye-tracking equipment) analyze the variable's large assortment, visual attention to SKU pricing, search effort and shopping frame time.

The results suggest that, although it increases the search effort, a large assortment decreases the visual attention to SKU pricing. Further, our results indicate a moderating effect associated with mitigating the negative effect by medium-low levels of search effort and a moderating impact of time in this relation.

Marketing professionals can carefully optimize the in-store experience by managing the assortment and variety and by influencing consumers' visual attention to SKU pricing along the journey as part of the experience. Assortment and SKU pricing strategies need to be aligned with consumer journey design.

Our findings contribute to assortment theory and management by detailing the relationship between consumers' reactions to assortment perception and visual attention to SKU pricing in time flow. We reinforce the importance of considering assortment strategies from the consumer perspective and giving reliable information about in-store behavior.

While few studies have examined business-to-business (B2B) mobile application (app) usage, none have examined the challenges in developing these technological assets. This study aims to examine B2B marketing executives’ perceptions regarding benefits, barriers and facilitators in app development.

A survey of 311 B2B marketing executives at selling firms in the USA was conducted to identify key themes related to the benefits, barriers and facilitators in developing B2B apps. The research featured “open-ended” questions exclusively, and advanced textual and thematic analysis of executives’ responses produced several key themes.

Results show that the perceived benefit of lowering customer servicing and costs drives development more so than trying to realize new revenue opportunities (e.g. “saving” vs. “making” money). Achieving internal buy-in/participation was perceived as a larger barrier than the commitment of financial resources. Additionally, training and education were viewed as the strongest facilitators of an app’s success over its design and functionality. Implications for B2B firms are discussed.

The open-ended format of this research captures a greater breadth of perspectives at the expense of more granular analysis of any particular issue.

The themes generated from the responses offer novel insights into the benefits sought in developing an app, as well as the technological, organizational and environmental factors that act as barriers and facilitators. The open-ended format of this research captures a greater breadth of perspectives at the expense of a more granular analysis of any particular issue.

The paper aims to provide a comprehensive analysis of artificial intelligence’s (AI) transformative impact on the real estate industry. By examining various AI applications, from property recommendations to compliance automation, this study highlights potential benefits such as increased accuracy and efficiency. At the same time, this study critically discusses potential drawbacks, like privacy concerns and job displacement. The paper's goal is to offer valuable insights to industry professionals and policy makers, aiding strategic decision-making as AI continues to reshape the landscape of the real estate sector.

This paper employs an extensive literature review, combined with a qualitative analysis of case studies. Various AI applications in the real estate industry are examined, including machine learning for property recommendations and valuation, VR/AR property tours, AI automation for contract and regulatory compliance, and chatbots for customer service. The study also delves into the optimisation potential of AI in building management, lead generation, and risk assessment, whilst critically discussing potential challenges such as data privacy, algorithmic bias, and job displacement. The outcomes aim to inform strategic decisions for industry professionals and policy makers.

The study finds that AI has significant potential to revolutionise the real estate industry through enhanced accuracy in property valuation, efficient automation and immersive AR/VR experiences. AI-driven chatbots and optimisation in building management also hold promise. However, this study also uncovers potential challenges, including data privacy issues, algorithmic biases, and possible job displacement due to increased automation. The insights gleaned from this study underscore the importance of strategic decision-making in harnessing the benefits of AI while mitigating potential drawbacks in the real estate sector.

The paper's practical implications extend to industry professionals, policy makers, and technology developers. Professionals gain insights into how AI can enhance efficiency and accuracy in the real estate sector, guiding strategic decision-making. For policy makers, understanding potential challenges like data privacy and job displacement informs regulatory measures. Technology developers can also benefit from understanding the sector-specific applications and concerns raised. Additionally, highlighting the need for addressing algorithmic bias and privacy concerns in AI systems may foster better design practices. Therefore, the paper's findings could significantly shape the future trajectory of AI integration in real estate.

The paper provides original value by offering a comprehensive analysis of the transformative impact of AI in the real estate industry. Its multi-faceted examination of AI applications, coupled with a critical discussion on potential challenges, provides a balanced perspective. The paper's focus on informing strategic decisions for professionals and policy makers makes it a valuable resource. Moreover, by considering both benefits and drawbacks, this study contributes to the discourse on AI's broader societal implications. In the context of rapid technological change, such comprehensive studies are rare, adding to the paper's originality.

This paper aims to investigate the influential aspects of industrial branding in building customer brand engagement from the buyer’s and the seller’s points of view. Collecting buyer and seller information is essential to understand business-to-business interaction better. Buyer’s and seller’s perspective integration is significant for stakeholders to develop proper strategies to achieve customer brand engagement.

This study uses a structural equation model to examine the antecedents of customer brand engagement from the buyer’s perspective; then, the result is compared with the seller’s view by conducting an analytical hierarchy process. The authors exercise 140 valid data from the buyer’s industry and 9 experts from the seller’s industry.

This study finds that in developing customer brand engagement, rational brand quality is the most influential from the buyer’s view and top priority from the seller’s view. Surprisingly, both parties have different perspectives about the second and third priorities. The buyers put emotional brand associations as a second priority; perceived value is meaningless and insignificant. On the contrary, the sellers set the perceived value as the second priority and emotional brand associations as the last.

The respondents from the buyer industry cover various industries, and the research is limited to the buyer and the seller in the chemical polymer emulsion market, a market where product quality and application quality on the buyers’ side are essential and where the buyer–seller interaction is intense. Replicating the study in other industries and cultural backgrounds is recommended for generalization.

The paper’s novelty is that there are different priorities and perspectives from the buyer’s and the seller’s views. This study contributes to industrial brand engagement research studies. Investigation of the buyer’s and the seller’s perspectives in industrial brand engagement research studies is still limited.

This paper aims to develop a house price forecasting model to investigate the impact of neighbourhood effect on property value.

Multi-level modelling (MLM) method is used to develop the house price forecasting models. The neighbourhood effects, that is, socio-economic conditions that exist in various locations, are included in this study. Data from the local government area in Greater Sydney, Australia, has been collected to test the developed model.

Results show that the multi-level models can account for the neighbourhood effects and provide accurate forecasting results.

It is believed that the impacts on specific households may be different because of the price differences in various geographic areas. The “neighbourhood” is an important consideration in housing purchase decisions.

While increasing housing supply provisions to match the housing demand, governments may consider improving the quality of neighbourhood conditions such as transportation, surrounding environment and public space security.

The demand and supply of housing in different locations have not behaved uniformly over time, that is, they demonstrate spatial heterogeneity. The use of MLM extends the standard hedonic model to incorporate physical characteristics and socio-economic variables to estimate dwelling prices.

This study aims to explore how social media affects decision-making among tourists and whether there is a potential effect of age, which is studied through generations. For this purpose, baby boomers, Gen X, Gen Y and Gen Z tourists are studied and real-time implications are offered.

The study adopts a descriptive and exploratory design where the conceptual model of social media-based decision-making is developed through a review of the literature. Quantitative analysis is conducted on primary data from 600 Indian tourists. This is done using a self-administered questionnaire adopted from Gulati (2022) after checking its validity and reliability. The statistical analysis for hypothesis testing is done using PLS-SEM path modelling on pooled data. To study the categorical moderating effect of generations, partial least squares multigroup analysis (PLS-MGA) is performed as a paired comparison on every successive generation.

After testing every successive younger generation with an older generation through PLS-MGA, none of the pairs found any significant differences in path coefficients, as the values obtained were 0.05 < p < 0.95 for all five paths (SM → NR, SM → IS, SM → E, SM → P, SM → PPB). This indicates all the generations behave in a similar manner irrespective of them being older or younger, and age does not moderate social media’s impact on decision-making among Indian tourists.

The study establishes India as a unique geographical market and suggests tourism marketers to treat all generations at par, irrespective of age, as they behave and interact with social media in a similar manner. But, because this study is restricted to a single geographical location, i.e. India, further regions can be explored for global generalisation. Future research can also explore other demographics for combined, moderated analysis. Findings from the study suggest that marketers should ensure that equal attention is given to all generations as they engage with social media in a similar manner. Targeted marketing using artificial intelligence can help in ensuring custom ads. Personalisation according to generations can also facilitate greater purchases.

The study fills a major population and knowledge gap by exploring a topic that has been highly under-researched. Also, the study adopts an inclusive approach by analysing all the generations, both younger and older, to understand the potential effect of age on moderating the impact that social media has on tourist decision-making. Further, real-time suggestions and implications are offered to tourism marketers with special reference to the Indian tourism industry.

Online impulsive purchasing is growing exponentially, and website-related factors play a substantial role in this phenomenon. This study provides a comprehensive and integrative framework encompassing a variety of website-related factors influencing impulsive purchase behaviour.

The study is a systematic literature review, which includes literature search from two prominent databases. This article consolidates the results of 60 relevant research papers, and thematic analysis is performed on various website-related aspects classified into five research topics.

The different website qualities have been classified into broad themes and their role in online impulse buying has been explored. The antecedents, moderators, mediators, and outcomes are portrayed in an integrated research framework. Possible research gaps have been identified, and a future research agenda has been proposed, representing potential research areas.

As we have included only studies published in the English language, this review may be limited by language bias. Relevant research published in other languages might have been excluded.

This literature review may provide management insights to marketers and practitioners managing online retail websites. To sustain an online business in the long term, it is critical for online retailers to have a thorough understanding of all conceivable website stimuli and develop them in a way that compels consumers to make impulsive purchases.

This study represents an original contribution to the realm of systematic literature reviews. To the best of our knowledge, this is the first SLR that elaborately delineates the influence of website-related factors on online impulse buying behaviour.