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Despite the extensive stimulus–organism–response (SOR) literature, little attention has been paid to the role of marketing activity as a key environmental stimulus, and there is a dearth of research examining the interplay between emotions and cognition on consumer behaviour, as well as the sequential effects of emotions on cognition. To address these gaps, this study aims to develop a revised SOR model by incorporating Kahneman’s fast and slow thinking theory to investigate the impulse buying of affordable luxury fashion (ALF).

The authors use outlet stores at Bicester village (BV) in England as the research context for ALF shopping. Partial least squares structural equation modelling was used to analyse a survey sample of 633 consumers with a BV shopping experience.

The authors find that impulse buying of ALF arises from the interplay of emotional and cognitive factors, as well as a sequential and dual process involving in-store stimuli affecting on-site emotion and in-store browsing.

This study reveals that brand connection has a significant and negative influence on the relationship between on-site emotion and in-store browsing, advancing the SOR paradigm and reflecting the interactive effect of human emotion and reasoning on the impulse buying of ALF items.

Insights into consumers’ impulse buying offer practical implications for luxury brand management, specifically for ALF outlet retailers and store managers.

The results suggest a robust sequential effect of on-site emotion towards in-store browsing on impulse buying, providing updated empirical support for Kahneman’s theory of System 1 and System 2 thinking.

While customer perceived augmented reality (AR) values have generally enhanced customer experience, AR value would be appreciated the most by a consumer segment that remains unexplored. Drawing from human value orientation theory and consumption value theory, this research proposes a new model analysing the effects of human value orientation (openness to change, conservation, self-transcendence, and self-enhancement) on perceived AR values (playful, social, visual appeal, usability) and subsequently the effects on customer satisfaction.

:The authors employed a two-step online data collection. The first step was to identify those who had used retailers' AR applications, who were then invited to participate in the full survey in the second step. A sample of 253 AR technology users' data was analysed using partial least square and structural equation modelling.

The results reveal that each human value orientation is associated with its unique perceived AR values and that various perceived AR values influence customer satisfaction differently.

This study shows the pivotal role human value orientation plays in influencing customer perceived AR values and their impacts on customer satisfaction. The findings offer key implications for digital marketing segmentation.

The purpose of this paper is to empirically explore the mechanisms through which Chinese National Science Parks' (NSPs) services facilitate returnee entrepreneurs' (REs) acquisition of resources for their new ventures. Resource acquisition is crucial for new ventures, but it inevitably leads to significant costs increase. Although the NSPs offer various services to REs to reduce these costs, they still struggle to find the right mix of services.

From the transaction cost's perspective, an exploratory multiple-case study was conducted with data collected from six NSPs in China.

The results reveal that four types of NSP services (mentoring and training, social event, promotion of REs and accreditation of resource holders (RHs)) have both individual and joint effects on reducing REs' resource acquisition costs. Specifically, the “accreditation of RHs” service directly helps REs reduce search costs. The combination of “accreditation of RHs”, “promotion of REs” and “social event” services help REs and RHs to establish guanxi. Further, guanxi, working along with the “mentoring and training” service, helps REs to reduce contracting, monitoring and enforcement costs.

This study is among the first to explore the matching mechanisms between science parks’ services and entrepreneurs' cost reduction. This helps reconcile the inconsistent findings on science parks' effect by explaining why some NSPs are able to provide strong support to REs while others are less successful. In addition, the findings are useful for NSPs to develop the right mix of tailored services for REs. Finally, REs will find this study useful to evaluate which NSP is a more suitable location for their new ventures.

Social media influencers (SMIs) play an increasingly important role in influencing youth and their shopping behaviours in digital marketing. Research has examined various but fragmented SMIs, which cause inconsistency in empirical results. This research seeks to categorise the most popular SMIs in luxury fashion and examine their distinctive effects on Gen Z consumption in China.

The authors categorise SMIs into four groups based on two dimensions, i.e. network interactivity vs social connectedness. Drawing on the social network theory, the authors develop the research model. A sample of 400 survey data is collected and analysed using the PLS-SEM technique.

The empirical results suggest that among the four popular SMIs groups, the effects of celebrities, opinion leaders and friends and peers on luxury fashion consumption of Gen Z are statistically significant while that of advertisers are insignificant; that friends and peers have the most substantial effect among the others.

The study contributes to understanding SMIs and consumer behaviour in digital emerging markets. By categorising SMIs, this study reconciles inconsistencies in the concept. This study contributes to a better understanding of SMIs and their roles in the digital marketing of luxury fashion consumption.

Despite extensive study into various aspects of corporate social responsibility (CSR), the effect on consumer behaviour is less explored. A growing amount of research is concerned with the phenomenon that CSR has a minor effect on actual purchases although CSR practices enhance consumers’ purchase intentions. This is documented as the CSR-consumption paradox and is yet to be resolved. The purpose of this paper is to further understand this paradox.

Questionnaires were administered face-to-face to consumers in Birmingham. These questionnaires concern consumer behaviour in relation to CSR practices of 21 popular apparel companies in the UK.

Results suggest that consumers’ pro-social priority is significantly related to pro-social consumption and that consumers’ awareness of CSR practices is insignificantly associated with their purchase behaviour. The pro-social consumption does not differ significantly among different demographic groups.

To explore the external motivational factors in consumers’ decision making will be a potential research direction in future.

The empirical results provide implications for UK apparel marketers and policy makers to engage and motivate socially responsible consumers so as to reap strategic rewards for their CSR efforts.

This paper contributes to the knowledge of socially responsible consumption and how it is affected by CSR.

Scholars have typically examined family business exposure as an aggregate variable. However, it is probable that this trend oversimplifies the complexity of family exposure and its nuanced influence on entrepreneurial behaviour. Thus, to extend the theoretical boundary, this inquiry investigates distinct dimensions of family exposure in Nigeria while drawing on the theory of planned behaviour.

Data were collected from five public universities in Nigeria. A sample of 1,314 respondents was analysed using a partial least squares structural equation modelling approach to determine the influence of alternate family business exposures.

The results show that entrepreneurial exposure in the forms of parent, family member and work involvement have salient and distinctive influences on implementation intention to the extent that entrepreneurial self-efficacy, attitudes and subjective norms are uniquely impacted.

This study offers novel insights on the predictors of entrepreneurial implementation intention through the distinctive effects of (1) family member exposure, (2) parent exposure and (3) work involvement exposure among students in the family firm context.

This paper aims to examine the impact of deregulation on the European transport industry in the form of privatization, on the managerial efficiency of a panel of deregulated transport companies.

This research examines a data set of 25 deregulated transport companies from a sample of 12 EU nations from 1988 to 2015. Some studies have analyzed deregulation by using non-parametric models. However, only a limited number of studies focus on the impact of deregulation on the managerial efficiency. This study answers two questions: whether deregulation, in the form of privatization, in the transport sector has any effect on the managerial efficiency, on the profitability and on the investment decisions of the firm, and whether this premise is robust enough across the European transport industry. This study formulates a multivariate regression framework utilizing data from major privatized European transport companies. The final panel includes 25 companies, from 12 EU - Member States for the period 1988-2015, equaling 375 firm-year observations based on a rigorous selection methodology.

The study confirms that transport companies, post-privatization, are more efficient regarding operating efficiency and profitability. The authors find no evidence that deregulation improves investment efficiency.

The study addresses the regulators’ dilemma, whether to deregulate, by focusing on analyzing the improvement of the managerial efficiency.

This study contributes to the transport industry management literature in three ways. First, the authors update the literature of the economic theory of regulation with an empirical examination which covers the latest years across the EU Member States. Second, the authors introduce a comparison of the effects of deregulation on different components of the managerial efficiency, namely, investment, profitability and operating efficiency of the incumbents in the EU transport industry. Third, they examine deregulation by using two approaches: a traditional one where deregulation is a dummy variable assessing the overall effect on incumbents’ efficiency performance; and a novel approach where the Organisation for Economic Co-operation and Development’s deregulation index is used to measure the regulation intensity, accounting also for industry-wide impact assessment. This two-sided approach increases the robustness of the results.

With the ever-expanding online shopping, electronic word-of-mouth (eWOM) has become a significant factor affecting the consumer decision-making behaviour. This is specially the case when considering Generation Y (Millennials), who are old enough to be independent buyers and young to be almost immersed in online living. This article aims to assess the impact of eWOM on purchase intention by developing a conceptual model of hypotheses encompassing a multitude of factors that may be associated with this relationship.

The researcher investigates what factors impact eWOM credibility and make the consumer may adopt it when making a purchase. To examine our research model, a quantitative approach is employed for this purpose using a sample through online survey from Thailand – where there is a large number portion Generation Y consumer base.

It was found that source style as a visual attribute information is the most significant factor that may impact eWOM credibility in addition to source credibility, argument quality and source homophily, respectively.

From a practical point of view, it helps firms to understand what needs to be taken into consideration when building their marketing strategy.

This is believed to add significant insights into the eWOM literature by identifying its route of impact toward the purchase intention on Generation Y.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

This study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.

This paper presents a new method, used to the collected corrosion data of carbon steel provided by the China Gateway to Corrosion and Protection, that combines non-linear gray Bernoulli model (NGBM(1,1) with genetic algorithm to attain the purpose of this study.

Results of the experiments showed that the present study’s method is more accurate than other algorithms. In particular, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method in data sets are 9.15 per cent and 1.23 µm/a, respectively. Furthermore, this study illustrates that model parameter can be used to evaluate the similarity of curve tendency between two carbon steel data sets.

Corrosion data are part of a typical small-sample data set, and these also belong to a gray system because corrosion has a clear outcome and an uncertainly occurrence mechanism. In this work, a new gray forecast model was proposed to achieve the goal of long-term prediction of carbon steel in China.