Abstract

Data analytics plays a significant role within the context of the digital business landscape, particularly concerning online sales, aiming to enhance understanding of customer behaviors in the online realm. We review the recent perspectives and empirical findings from several years of scholarly investigation. Furthermore, we propose combining computational methods to scrutinize online customer behavior. We apply the decision tree construction, GUHA (General Unary Hypotheses Automaton) association rules, and Formal concept analysis for the input dataset of 9123 orders (transactions) of sports nutrition, healthy foods, fitness clothing, and accessories. Data from 2014 to 2021, covering eight years, are employed. We present the empirical discoveries, engage in a critical discourse concerning these findings, and delineate the constraints inherent in the research process. The decision tree for classification of the year’s fourth quarter implies that the most important attributes are country, gross profit category, and delivery. The classification of the morning time implies that the most important attributes are gender and country. Thus, the potential marketing strategies can include heterogeneous conditions for men and women based on these findings. Analyzing the identified groups of customers by concept lattices and GUHA association rules can be valuable for targeted marketing, personalized recommendations, or understanding customer preferences.

Introduction

Analyzing consumers’ online purchasing habits can provide many advantages for commercial entities, marketing professionals, and consumers. Classifiers based on decision trees can be applied to predict market trends, specifically for determining when to buy or sell. Decision trees are the transparent and efficient option for machine learning because they sort data attributes at each node to arrive at a decision (Samarth 2023; Vaca et al. 2020). Several researchers proposed a system to enhance the shopping experience at fashion retail outlets. This system smartly groups together various items and customer profiles, which it encounters online and in physical stores. It leverages the power of mining association rules to foresee the shopping patterns of new customers (Bellini et al. 2023; Fan et al. 2023).

Formal concept analysis (FCA) (Carpineto and Romano 2004; Ganter and Wille 1999; Poelmans et al. 2013) is a method of data analysis based on a lattice theory that has great potential to study how people behave online. This method offers visualization capabilities to explore the relationships in the object-attribute tables that are present, for example, by customer transactions and their characteristics. Combining well-known methods like decision trees and pattern-finding has made these studies more attractive to a broader audience.

Conclusion

In this paper, we presented the analysis of real e-shop consumer behavior data in eastern Europe, which contains data from 9123 orders of sports nutrition, healthy foods, fitness clothing, and accessories from 2014 to 2021. For analysis, we applied the methods of decision trees, GUHA association rules, and Formal concept analysis. We found that each of these methods provides various possibilities to have a greater look at consumer behavior of online e-shops.

Abstract

Social media marketing has become a crucial component of contemporary business strategies, significantly influencing brand visibility, customer engagement, and sales growth. The aim of this study is to investigate and determine the key factors guiding customer attitudes towards social media influencers, and, on that basis, to explore their effects on purchase intentions regarding advertised products or services. A total of 376 filled-in questionnaires from an online survey were analysed. The main characteristics of digital influencers’ behaviour that affect consumer perceptions have been systematized and categorized through a combination of both traditional and advanced data analysis methods. Structural equation modelling (SEM), machine learning and multi-criteria decision-making (MCDM) methods were selected to uncover the hidden dependencies between variables from the perspective of social media users. The developed models elucidate the underlying relationships that shape the acceptance mechanism of influencers’ messages. The obtained results provide specific recommendations for stakeholders across the social media marketing value chain. Marketers can make informed decisions and optimize influencer marketing strategies to enhance user experience and increase conversion rates. Working collaboratively, marketers and influencers can create impactful and successful marketing campaigns that resonate with the target audience and drive meaningful results. Customers benefit from more tailored and engaging influencer content that aligns with their interests and preferences, fostering a stronger connection with brands and potentially affecting their purchase decisions. As the perception of customer satisfaction is an individual and evolving process, stakeholders should organize regular evaluations of influencer marketing data and explore the possibilities to ensure the continuous improvement of this e-marketing channel.

Introduction

Social media influencers, also referred to as digital influencers, online influencers or internet influencers, came into prominence at the beginning of the 21st century, during the transition from the early Web 1.0 environment to the collaborative Web 2.0 era. Initially, companies only sought celebrities to stimulate successful product sales. Today, online influencers are key figures who attract and captivate audiences with their specialized knowledge or intriguing lifestyle, making them valuable assets for brands when establishing a strong online presence [1]. Influencer marketing is a form of internet advertising that builds brand loyalty based on the reputation, recommendations, and popularity of a given celebrity or well-known personality [2]. The rise of social media has turned influencer marketing into a preferred tool for brand awareness and sales promotions.

The COVID-19 health crisis has been one of the catalysts for technological advancements in marketing strategies. As people spent more time online due to lockdowns and restrictions, online influencers became key marketing instruments for brands to connect with their target audiences. The pandemic led to a greater proliferation of social media influencers as sources of information and product recommendations [3,4].

According to Statista’s analysis [5], the global influencer marketing market was valued at USD 21.1 billion as of 2023, representing a substantial increase of 224.6% from the pre-pandemic level of USD 6.5 billion in 2019 and a 28.7% increase from the previous year’s level of USD 16.4 billion in 2022. As per the Influencer Marketing Hub report [6], the influencer marketing industry is projected to reach around 24 billion by the end of 2024. In this report, nearly a quarter of the surveyed participants planned to allocate over 40% of their total marketing budget to influencer campaigns. This growth underscores the importance of influencer marketing as a communication channel for reaching and engaging audiences.

Conclusions and Future Research

Social media marketing has revolutionized business–customer interactions, providing various platforms for online engagement. By delivering valuable content in an interactive manner, social media influencers bridge the gap between brands and consumers, empowering companies to transform their advertising strategies and extend their reach beyond geographical constraints. This digital marketing tool enhances business-to-customer relationships by facilitating collaboration and efficiency in interactions.

In this study, we explore the characteristics of social media influencers, highlighting their transformative effect on brand perception and consumer behaviour. The key findings are outlined below:

The changing dynamics of consumer behavior in today’s digitally driven market presents opportunities and challenges for sustainable marketing development [1]. There is a growing awareness that consumer choices have a significant effect on the planet’s health as society struggles with urgent environmental issues like deforestation, climate change, and plastic pollution [2,3].

In particular, how individuals, groups, or organizations purchase, utilize, or discard ideas, products, services, or experiences to fulfill their needs and demands is referred to as consumer behavior [4]. Before making decision on what to buy, consumers undergo a number of emotional, social, and psychological processes [5]. Creating, communicating, and delivering value to customers in a way that acknowledges and addresses the long-term effects of these practices on economic, environment, and societal well-being are all part of what are known as sustainable marketing practices [6]. Park et al. [7] stated that sustainable marketing merges elements of green, social, and environmental marketing. Additionally, it is a strategy that benefits both the environment and businesses by creating goods and services that are both socially responsible and environmentally friendly, as they have eco-friendly attributes [8]. These qualities help with fostering brand loyalty and ensuring optimal practices.

This Editorial examines the crucial nexus that exists between consumer behavior and sustainable marketing practices, highlighting the importance of having a strong grasp of how these practices appear in online and offline contexts. The COVID-19 pandemic accelerated the rise in online shopping, which has changed consumer expectations and behaviors [9,10]. This transformation of shopping in the digital realm provides an unparalleled opportunity for companies to develop sustainable marketing strategies such as using environmentally friendly packaging and carbon-neutral shipping methods and promoting digital merchandise [11]. Nevertheless, it also introduces new obstacles, including the rise in packaging waste and the environmental impact associated with the transportation of goods [12,13]. In this vein, creating effective sustainable marketing strategies that reduce a firm’s environmental impact requires understanding consumer preferences and behaviors in the digital sphere [14,15].

On the other hand, the offline retail setting is still crucial for encouraging eco-friendly consumer behaviors. Offline stores provide customers with real-time experiences that can impact their decisions, such as the chance to interact with eco-friendly products or take part in recycling initiatives [16]. Additionally, retailers can utilize these interactions to impart knowledge to consumers about sustainability, thereby encouraging responsible consumption patterns [17,18]. Moreover, direct consumer behavior in an offline environment yields insightful information that can guide sustainable marketing strategies in both offline and online contexts [19,20,21].

Jo [22] emphasized that a comprehensive approach that takes into account the nuances of consumer behavior in both digital and physical domains is imperative for the development of sustainable marketing practices. It entails not only promoting sustainable goods and services but also developing an ecosystem that supports and makes making sustainable decisions easier. This entails using social media platforms to spread awareness of sustainability issues, tailoring marketing messages toward environmentally conscious consumers, and leveraging data analytics to understand consumer preferences [23,24].

Furthermore, companies need to understand the importance of authenticity and openness to gaining the trust of customers [25]. Customers’ awareness is rising, and they are becoming less trusting of greenwashing strategies [26]. They demand an authentic dedication to sustainability, demonstrated by tangible deeds and quantifiable results [27]. As a result, businesses need to make sure that their marketing messages highlight their commitment to environmental sustainability and are consistent with their operational procedures. Due to the complex relationship between consumer behavior and sustainable marketing practices, a thorough investigation is necessary to assess the relationship empirically. This highlights the importance of having a nuanced understanding of how these practices appear in both online and offline contexts.

Abstract

A blue jeans brand committed to the environmental cause could position itself as unique and socially responsible and attract environmentally driven consumers. This research study examines the relationship between brand love and consumers’ environmental cause knowledge and their willingness to recommend and pay a premium for sustainable blue jeans. To this end, this cross-sectional study comprises a snowball convenience sample of 978 Portuguese respondents, whose data were collected from December 2022 to January 2023. Positive associations between self-expression, brand love, loyalty, environmental cause knowledge, positive word-of-mouth, and willingness to pay a premium for sustainable blue jeans stand out. There are differences in the willingness to pay a premium among generations, education levels, and consumers who are aware of sustainable line extensions and those who are not. The results may be helpful for brands, suggesting their communication should focus on creating increased proximity to consumers by enhancing their values and seeking to link their brands to intrinsic benefits and environmental stakes. This is the first study to incorporate knowledge of the environmental cause into a model linking brand love, brand loyalty, positive word-of-mouth, and willingness to pay a premium for sustainable blue jeans.

Introduction

The environmental impacts of the fashion industry are widespread and significant, as the industry is a heavy water consumer (approximately 79 trillion liters per year), producing 8 to 10 percent of the global CO2 emissions and large amounts of textile waste, most of which ends up in landfills or is incinerated, including unsold products [1].

In addition to being globally popular, blue jeans are associated with somewhat problematic sustainability and social responsibility issues [2]. The traditional jeans production process uses excessive amounts of water, chemicals, and energy, thereby generating a negative impact regarding the carbon footprint [3]. In order to remove excess dyes and achieve the desired color, blue jeans are washed at least twice before being sold; globally, approximately 3% of the water used in agriculture goes into cotton production [4] to produce more than 2 billion units per year [5]. Another factor contributing to environmental degradation comprises the chemical products used throughout the production process (from insecticides and pesticides), even in cotton production, which accounts for 2.4% of the world’s arable land use; other chemicals are used to dye and paint the jeans, which have a significant environmental impact if not properly handled and disposed of in the environment [6].

Conclusions

The work carried out in this study allowed us to find a model that fit the data for 978 respondents to verify the results reported in the literature among Portuguese consumers of blue jeans, namely the positive associations of identification with brand love; of brand love with brand loyalty, positive word-of-mouth, and willingness to pay a premium for sustainable blue jeans; and of knowledge of the environmental cause with willingness to pay a premium for sustainable blue jeans. It was also concluded that there were no significant gender differences in terms of positive word-of-mouth and willingness to pay a premium for sustainable blue jeans. Members of generation Z and consumers with higher education levels are more willing to pay a premium for sustainable blue jeans than their counterparts.

It was also found that consumers who were aware of sustainable blue jeans alternatives from their preferred brands had significantly higher scores for all variables in the model, suggesting that this awareness may be associated with greater knowledge of the environmental cause, which is critical in explaining the greater levels of identification, brand love, and brand loyalty, and the resulting intention to spread the good word and willingness to pay a premium for sustainable blue jeans.

The positive impacts of brand love on brand loyalty, word-of-mouth, and willingness to pay a price premium was further acknowledged according to the literature findings. To the best of the authors’ knowledge, this study is the first to incorporate knowledge of environmental causes in a model that relates brand love to brand loyalty and the latter to positive word-of-mouth and willingness to pay a premium, as tested by Caroll and Ahuvia [27] and Albert and Merunka [24], applied here to the Portuguese market and focused on sustainable blue jeans. This approach, thus, incorporates Bagozzi et al.’s [26] suggestion to develop models in which brand love is central to other dimensions, thereby contributing to the academic literature. The findings also have practical implications for blue jeans brands as they enhance the importance of creating awareness of the existence of sustainable extension lines, as well as of conveying a true environmental concern to capture environmentally driven consumers that would be willing to pay a premium for sustainable blue jeans, namely by focusing on creating increased proximity to consumers by enhancing their values and seeking to link the brand to intrinsic benefits and environmental stakes.

Abstract

Using a proprietary dataset from an Australian leading FinTech lender, we provide insights into the effect of consumer behaviour on FinTech lending patterns. Out of seven consumption categories, gambling expenses significantly reduce the lender’s willingness to fulfill loan requests. Cash usage and repeated borrowing are related to lower offer-to-requested loan ratios. The FinTech lender prefers to lend to borrowers who are married, have dependents and/or aged over 30. However, for such mature borrowers, cash usage and repeated borrowing increasingly reduce the approval likelihood of their loan requests. Taken together, our empirical evidence suggests that consumer behaviour affects FinTech lending decisions.

Introduction

In this study, we provide new evidence on the relationship between consumer behaviour and credit access using a novel data by a leading Australian FinTech lender specialized in short-term consumer credit products. FinTech firms have garnered increasing attention amongst policy makers and regulators given its disruption to how traditional businesses are conducted in the consumer credit market, particularly through open banking initiatives. Jagtiani and Lemieux (2019) show that FinTech lenders utilize more soft information from alternative data sources in screening and this business process benefits borrowers who would otherwise be unable to obtain credit. Di Maggio and Yao (2021) investigate FinTech lenders’ pricing strategies and borrower outcomes using a large dataset on household balance sheets. They find that FinTech lenders rely on hard information from credit reports rather than soft information or alternative data.

We contribute to this growing literature by presenting novel evidence on how soft information from bank statements surrounding payment and consumption behaviours affects the willingness of FinTech lenders to fulfill loan requests. Prior studies have shown some alternative data, such as applicant’s appearance, social network and writing style, etc., used in FinTech lending (e.g., Herzenstein et al., 2011; Lin et al., 2013; Gonzalez and Loureiro, 2014; Dorfleitner et al., 2016; Freedman and Jin, 2017; Buchak et al., 2018; Jiang et al., 2018; Croux et al., 2020). Our unique dataset allows us to show that FinTech lender’s willingness to supply credit depends on the consumer behaviour revealed from information contained in bank statements and applicant demographics. Moreover, to the best of our knowledge, we are amongst the first to study the effect of consumer behaviour on FinTech lending, while most extant studies focus on the implications of FinTech lending on borrowers (e.g., Gathergood et al., 2019; Di Maggio and Yao, 2021) or the prediction of defaults (e.g., Khandani et al., 2010).

Conclusion

This study examines the relationship between consumer behaviour and credit access using a novel data by a leading Australian FinTech lender specialized in short-term consumer credit products. Our findings provide an Australian perspective to the growing literature on FinTech lending which uses primarily U.S. data. Our unique dataset reveals that FinTech lender’s lending decisions depend on loan applicants’ consumer behaviour. To the best of our knowledge, we are amongst the first to study the effect of consumer behaviour on FinTech lending, while most studies focus on the implications of FinTech lending on borrowers (e.g., Gathergood et al., 2019; Di Maggio and Yao, 2021) or the prediction of defaults (e.g., Khandani et al., 2010).

This study has its limitation. Due to the data constraint, we can only show the association, but not causal relation, between loan applicant’s consumer behaviour and FinTech lending. Nevertheless, we believe that the findings on the association between consumer behaviour and FinTech lending may still be of interests to FinTech borrowers, academics, and/or regulators. For example, our findings suggest that in the FinTech era, loan applicants need to be aware that their cash usage and gambling expenses can affect their borrowing capacity.

Abstract

The circular economy (CE) has emerged as a sustainable alternative to the linear model of production and consumption of products and services. Consumers are key actors in the circular economy loop, yet consumer behaviour and decision-making remain at the periphery of research in this area. To close this gap and to promote related academic research we perform a systematic literature review, analysing the main areas of research in the CE relating to consumer behaviour and decision-making. The results show that there are six main areas that link consumer and CE: consumer behaviour, purchase intention and sustainable consumption; lifetime and reparability; recycled plastics, upcycling, e-waste and innovation. These areas seem incomplete and focused on a relatively small number of sectors. Further, while attitude and knowledge are the most influential elements in the consumer’s buying decision-making process, our analysis shows significant gaps in current research in this regard. A key element of consumer behaviour, the post-purchase phase relating to “use”, “recycle” and “upcycle” was found to still be obscure. We provide recommendations on how this gap can be filled.

Introduction

The circular economy (CE) has been gaining increasing attention in recent years from society, companies and public bodies (Korhonen et al., 2017). The best-known economic model until now was the linear model, based on continuous growth and the use of many resources (Kirchherr et al., 2017; Ness, 2008). The CE has emerged as an alternative to this model, due to the fundamental positive role it plays in the environment, its functions and its interactions with the economic system (Ghisellini et al., 2016). The concept of CE has been reformulated and analysed several times in recent years (Geissdoerfer et al., 2017; Ghisellini et al., 2016; Kirchherr et al., 2017; MacArthur et al., 2013; Prieto-Sandoval et al., 2018), with researchers agreeing that it is a regenerative production and consumption model. However, it cannot be regarded as an individual process, as the CE involves a change in companies, industries and the economy through shifts in values, norms, behaviours and attitudes in society (Chizaryfard et al., 2021).

To this effect, the concept of CE is being analysed from different fields such as economics, strategy, engineering and resource consumption (Clube and Tennant, 2020; Demirel and Danisman, 2019; Machado et al., 2019; Perez-Castillo and Vera-Martinez, 2021), although there are still few studies concerned with the impact of consumers on the CE loop. Consumers must be involved in the whole process and be aware of the value of CE-based products and services. However, as stated by (Kirchherr et al., 2017), the reasons why consumers do or do not take part in CE processes have not been sufficiently analysed (Camacho-Otero et al., 2018). established that although there is increasing research on consumption, the contributions often refer to possible solutions relating to the nature or meaning of CE or the consumption progress, but do not focus on the relationship between the CE and the consumer. In turn (Wastling et al., 2018), argued that the role of the consumer in the CE needs to be questioned and has not yet been fully explored. To this end, there is a need to analyse the role of consumers to resolve the existing gaps in the current literature. However, not only is the relationship between CE and consumer essential to understand, but so are the behaviours and attitudes that consumer may have regarding this process, considered a hot topic due to the wealth of information it brings to both companies and society (Stankevich, 2017). The consumer can be analysed effectively through the decision-making process, wherein the consumer is at the centre (Zhang and Benyoucef, 2016).

Discussion and conclusions

Based on this literature review, it was found that interest in the relationship between the CE and the consumer has increased in the last two and a half years, when 75% of the documents analysed were published. This reflects the fact that it is a new topic that has a long way to go, and one that is important not only at European but also at global level. This literature review provided an overview of and revealed the deep research in the existing literature regarding the CE and the consumer, in terms of consumer behaviour and consumers’ PI.

To answer the first research question – What are the main areas of research in the CE relating to consumer behaviour? – this paper summarises and interrelates the different main areas of the CE with the consumer. Notably, seven different main areas were detected, all of them interrelated, as shown in Fig. 7. A circular economic model is presented, composed of “take, make, distribute, purchase, use and dispose”, adding “recycle, upcycle and innovate”. The CE was the main concept analysed, from which six different main areas were obtained that can be connected to the circular chain in terms of consumer behaviour. They were (1) the elements that affect consumers’ behaviour, PI and sustainable consumption; (2) lifetime extension and reparability; (3) packaging and recycled plastic; (4) e-waste; and (5) upcycling. Moreover, it was identified that process improvement and involvement depend on (6) innovation, as a way to reduce barriers to CE adoption and to contribute to a more sustainable economy, and so is considered a key factor within the CE loop. Each of the areas mentioned, except for the “purchase” area, which deals with the key concepts of consumer behaviour and attitudes, analyse consumers in a superficial manner, focusing more on the product or service than on consumer reactions or behaviours. To this effect, an important gap is detected in the literature, and that is the lack of knowledge of consumers in actions such as decisions to extend the life of a product, how consumers perceive the changes in new consumption models, and even how they can be re-educated in relation to concepts based on the CE.

Abstract

The dark side of customer behavior has been receiving increasing attention in the business and management literature in recent years. Scholars have used various terminologies to study those customer behaviors that disrupt service delivery, affect organizational performance, and impact on employees’ well-being. In this study, through a systematic literature review and bibliometric analysis of 246 academic articles, we identify three clusters within the dark side of customer behavior literature: (1) customer dysfunctional behavior; (2) customer revenge and rage as forms of customer misbehavior; and (3) customer mistreatment and incivility-related clusters. Based on these three identified clusters of the literature, we propose an integrative framework of customer incivility as customer incivility is the current centerpiece of the literature on the dark side of customer behavior. In doing so, we identify various research gaps and suggest effective avenues for future works in this research stream.

Introduction

In a customer-centric approach, serving customers and consumers effectively remains the cornerstone of successful business outcomes such as high firm performance, stronger brand value, and customer loyalty (Gupta & Ramachandran, 2021). Nevertheless, this shift towards customer-centricity also brought along detrimental customer behaviors. Hence, nowadays firms seek to understand how to deal with an increasing number of negative behaviors from customers as these negatively affect business outcomes as well as employees’ performance and psychological well-being (Hur et al., 2015, Yagil, 2017).

In this paper, we refer to these negative behaviors by using an umbrella term, the dark side of customer behavior, inspired by the dyadic relationship that exists between the “light” and the “dark” side of the Force in George Lucas’ creation Star Wars, and that is also represented in Western and Eastern philosophical and religious worldviews (Eberl, 2016) as well as in management literature (a couple of examples are the work of Davenport et al., 2007, Heidenreich et al., 2015 that conceptualized dark sides of different management processes and outcomes).

The dark side of customer behavior is an umbrella term for various concepts that scholars in consumer research and organizational research have used to define negative behaviors of consumers and customers. For example, Lovelock (2001) coined the term jay-customers for those customers who act inconsiderately, in a vulgar manner, and cause problems for the organization, other customers, and employees. The term dysfunctional customers is also used when investigating the behaviors of those individuals who deliberately or unintentionally, overtly or covertly disrupt the otherwise functional service delivery process (Fullerton and Punj, 2004, Harris and Reynolds, 2003). Other scholars coined the terms customer revenge and retaliation (e.g. Funches et al., 2009, Grégoire et al., 2010), which are seen as the cognitive, emotional, and behavioral efforts of customers in redistributing justice and fairness, and in punishing a corporation for its wrongdoings.

Conclusions

In this article we provided further clarity on the dark side of customer behavior. Our findings show that the dark side of customer behavior has been a prolific field of research across multiple disciplines beyond business and marketing research. Indeed, the topic has been examined through the lenses of psychology, organizational management, and sociology, and in varied sector studies such as hospitality.

The bibliometric analysis uncovered the development of the dark side of customer and consumer behavior research between 1976 and 2022. An assessment of the number of published articles over time, as well as the performance of authors, institutions, journals, and countries, has been performed. The findings from this analysis show that researchers in the United States, Australia, and China are the ones that have been more active in investigating this phenomenon. Furthermore, co-citation networks have been developed and analyzed to understand how the dark side of customer behavior field is structured. The Journal of Business Research emerged as a pivotal journal in this field.

Abstract

Keywords

1. Introduction

2. Literature review

3. Method

4. Analysis and results

5. Discussion

6. Implications

Funding

References

Abstract

Drawing on service encounters and experiential marketing theories, this study examined the relationship between geriatric service, memorable experience, emotional intelligence, and senior customers’ attitudinal and behavioural responses. The research was conducted at geriatric hotels in Portugal. The results showed that, compared to impersonal encounters, employee service has a significantly greater effect on customer satisfaction, memorable experience, and customer loyalty. In addition, customers’ memorable experiences mediated the relationship between different service encounters and organisational outcomes. However, customers’ emotional intelligence had minimal effects on these relationships. The discussion and implications of these findings are offered to researchers and practitioners.

1. Introduction

An increase in the ageing population drives the demand for retirement accommodations of senior citizens, which generally include retirement villages/homes and aged care homes (Cheek et al., 2007). While being different in terms of care options (self-care vs nursing care) (Yeung et al., 2017), facilities, and funding (self-funding vs government subsidised), retirement villages and aged care homes are often integrated with facilities catering to all senior citizens, who can opt for short- and/or long-term stay in some countries (e.g., Portugal). This integrated entity or accommodation is referred to as a geriatric hotel for this study. Recently, more geriatric hotels have sprung along with the increase in the aged population, which provides more options for senior citizens; simultaneously, it has driven competition among the hotels. Like in any other business, the key strategy to gain competitive advantage for a service provider or organisation is to attain customer satisfaction and loyalty (Prentice, 2014), which has become a performance metric for most service organisations and is referred to as organisational service performance (see Prentice, 2019a).

The antecedents of customer satisfaction and loyalty have been extensively discussed across industries and contexts in the relevant literature. From the perspective of service organisation, providing quality service is one of the most effective initiatives used to satisfy customers and generate customer loyalty and retention. Numerous studies have provided empirical evidence of a chain relationship between service quality, customer satisfaction, and loyalty (e.g., Olorunniwo et al., 2006; Prentice, 2013a, 2014; Shi et al., 2014). However, service quality is not necessarily directly related to customer satisfaction, as the level of overall quality service is expected unless some service elements (tangible or intangible) exceed customer expectations and are transferred into memorable experiences (Prentice, 2013a, 2014). Consumers opt to purchase and consume the service to acquire such experiences (Sandstrom ¨ et al., 2008). These memorable events that occur during service encounters affect their attitudes (e.g., satisfaction) and behaviours (e.g., purchase, loyalty behaviours) toward the service provider (Williams et al., 2020). Therefore, customers’ memorable experiences likely play a role in the relationship chain of service quality, customer satisfaction, and loyalty.

Abstract

1 | INTRODUCTION

2 | THE CENTRAL PROPOSITION

3 | DECISION-MAKING SHOULD BE VIEWED AS FOCUSSED ON ADDRESSING GOAL-RELATED PROBLEMS RATHER THAN IN TERMS OF UTILITY MAXIMIZATION

4 | THE CHARACTERISTICS OF PROBLEMS AND SOLUTIONS ARE NOT SELF-EVIDENT; CHARACTERIZATION IS AN ACTIVE PROCESS OF MAKING CONNECTIONS

5 | EXCEPT WHERE CONSTRAINED BY LACK OF IMAGINATION, HUMAN DECISIONMAKING USUALLY NECESSITATES THE USE OF STOPPING RULES AND SHORTCUTS TO PREVENT DECISION PARALYSIS OR DYSFUNCTIONAL DELAYS IN CHOOSING

6 | PEOPLE ARE NOT ALWAYS OPEN TO COMPENSATION-BASED INDUCEMENTS TO CHANGE THEIR BEHAVIOUR, FOR SOME CHANGES MAY CONFLICT WITH THEIR OPERATING RULES REGARDLESS OF THE COMPENSATION THAT WOULD ACCOMPANY THESE CHANGES

7 | THE BEHAVIOUR OF CONSUMERS CAN BE PREDICTED, AT LEAST PROBABILISTICALLY, IF THEIR OPERATING RULES CAN BE UNCOVERED

8 | CONCLUDING DISCUSSION

REFERENCES

Abstract

This article sets out a unified behavioural research programme that integrates compatible elements of old, new and evolutionary behavioural approaches to economics as an alternative to the dominant unified approach to economics based on rational choice theory and a Walrasian view of market coordination. However, the proposed programme can also be viewed as a general framework for interdisciplinary research on consumer behaviour. It employs the view of scientific research programmes proposed by Lakatos, setting out groups of ‘hard-core’ propositions and their associated ‘do’ and ‘do not’ rules for the conduct of researchers. The unifying theme is that evolution in the economy (and in human systems more generally) entails the creation, adoption and abandonment of rules for dealing effectively with open-ended choice problems that are bedevilled by infinite regress problems and cognitive challenges that people seek to address via personal repertoires of hierarchically related rules. To anticipate behaviour, researchers need to develop knowledge of these rules (including heuristics and routines), their functionality and the processes by which they get changed or prove difficult to change even where they cause problems.

1 INTRODUCTION

This article sets out a unifying framework for understanding and studying behaviour in socio-economic systems. The framework is conducive to interdisciplinary behavioural research, and it could be used in applied fields as diverse as economics, marketing, criminology, public health policy and social policy. However, in calling it the ‘ONE behavioural’ approach, I am using the upper-case ‘ONE’ as an acronym that alludes to its origins and role in relation to behavioural economics: it entails a synthesis of compatible ideas from what are classified later in this introduction as ‘Old’, ‘New’ and ‘Evolutionary’ strands of behavioural economics, and it is offered as a means by which economics might become ‘behavioural’ in a more ambitious and more methodologically coherent way than has been evident over the past four decades. When applied to economics, the ‘ONE behavioural’ research programme offers a means for addressing the discipline’s traditional concerns with issues pertaining to the allocation of scarce resources. However, it entails viewing consumer behaviour in a way that overlaps considerably with how it has been viewed in marketing, a discipline that focuses on different issues and has historically been much more open than economics to taking a highly interdisciplinary approach to understanding consumer behaviour. Indeed, differences between those who focus on ‘economic’ issues and those who focus on ‘marketing’ issues in how they seek to make sense of consumer behaviour could vanish if researchers in marketing also adopt the ‘ONE behavioural’ approach as an organizing framework for their work. If they do so, they will find that it can readily accommodate much of the existing marketing literature on consumer behaviour.

Abstract

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Abstract

This empirical research investigated the structural relationships between social media influencer attributes, perceived friendship, psychological well-being, loyalty, and perceived social responsibility of influencers, focusing on the perspective of social media users. More specifically, this study conceptually identified social media influencer attributes such as language similarity, interest similarity, interaction frequency, and self-disclosure and examined the respective effects of each dimension on perceived friendship and psychological well-being, consequently resulting in loyalty toward social media influencers. The authors collected and analyzed data from 388 social media users in the United States via Amazon’s Mechanical Turk with multivariate analyses to test the hypothesized associations among the variables in this study. The findings indicated that perceived friendship was significantly influenced by language similarity, interest similarity, and self-disclosure, but did not have a significant impact on psychological well-being. Additionally, perceived friendship significantly affected psychological well-being and loyalty, and psychological well-being significantly influenced loyalty. Lastly, social media influencers’ social responsibility moderated the path from psychological well-being to loyalty. Based on these findings, this study proposes theoretical and managerial implications for the social media influencer marketing context.

1. Introduction

Social media use is widespread and has been shown to play an important role in the lives of both adolescents and young adults [1]. Social media platforms enable adolescents and young adults to consume digital content without time and space limits and to virtually interact with other users without geographical boundaries [2]. Particularly, the development of digital platforms leads young adults to closely interact with their favorite celebrities, brands, and other users in the virtual world via two-way communication tools, such as live chats and comment options [3]. Interestingly, as social media platforms have grown, the digital world created a new phrase, “social media influencers,” who become famous through their digital content on social media, compared to traditional celebrities who become famous on TV shows and film [4]. Hence, social media users tend to feel connected with social media influencers by interacting with them in the virtual world and perceive social media influencers as more authentic in their fields, including fashion, health, or music, than celebrity endorsements in traditional advertisements [1]. Therefore, there is a need to empirically investigate what drives social media users’ loyalty toward their favorite influencers, such as repeat purchase behavior, positive word-of-mouth, and recommendation of products advertised by social media influencers from the perspectives of an influencer’s digitalized attributes [5,6]. These perspectives are especially important because social media users interact with their favorite influencers in the digital world instead of in the real world. This means that social media influencers’ digitalized attributes can be more important determinants of users’ perceptions, feelings, behavioral intention, and even actual behaviors than the visual characteristics of social media influencers. However, prior research in this field focused primarily on the visual and/or actual characteristics of social media influencers (e.g., physical attractiveness or social attractiveness) to predict marketing outcomes, such as positive attitudes toward and favorable intention for a product advertised by the influencers [7]. In particular, loyalty toward social media influencers leads followers to have a strong sense of product/brand association and reality by perceiving influencers’ product/brand and advertisements as more persuasive and authentic [4]. Accordingly, users are more likely to behave favorably for the product/brand social media influencers advertise in order to endorse the influencers and support the influencers’ fame and social status [7].

Abstract

1. Introduction

2. Literature Review and Hypotheses Development

3. Research Method

4. Results

5. Discussion

6. Conclusions, Managerial Implications, Limitations, and Suggestions

Appendix A

References

Abstract

     The purpose of this paper is to reveal how social network marketing (SNM) can affect consumers’ purchase behavior (CPB). We used the combination of structural equation modeling (SEM) and unsupervised machine learning approaches as an innovative method. The statistical population of the study concluded users who live in Hungary and use Facebook Marketplace. This research uses the convenience sampling approach to overcome bias. Out of 475 surveys distributed, a total of 466 respondents successfully filled out the entire survey with a response rate of 98.1%. The results showed that all dimensions of social network marketing, such as entertainment, customization, interaction, WoM and trend, had positively and significantly influenced consumer purchase behavior (CPB) in Facebook Marketplace. Furthermore, we used hierarchical clustering and K-means unsupervised algorithms to cluster consumers. The results show that respondents of this research can be clustered in nine different groups based on behavior regarding demographic attributes. It means that distinctive strategies can be used for different clusters. Meanwhile, marketing managers can provide different options, products and services for each group. This study is of high importance in that it has adopted and used plspm and Matrixpls packages in R to show the model predictive power. Meanwhile, we used unsupervised machine learning algorithms to cluster consumer behaviors.

Introduction

     With the advent of social networks, a lot of changes have happened in the marketplace. Nowadays, social networks (SN) have become the preferred platform of shopping for many consumers. Social networks make interactive communication among users and create substantial opportunities for marketers to connect with consumers [1].

     Facebook is the prime social network service in the world and a tool that has become an important part of consumers’ lives [2]. Facebook users, especially, tend to create commercial groups that allow them to conduct business. This kind of group that enables users to conduct consumer-to-consumer commercial activities is called a marketplace [3]. The marketplace is a kind of group which Facebook users create to sell their items. Many developed and developing countries are using social media platforms for purchasing products. COVID-19 has also significantly impacted the influence to purchase products in marketplaces. Moreover, popular social networks, such as Facebook and Twitter, are used by marketers to draw attention to their products and services and reach out to the customers [1,4]. Social networks marketing (SNM) has the potential to optimize the customer experience and journey [5], provide connection with customers [6], lower the marketing cost [7], and enable marketers to send messages to millions of consumers simultaneously [8]. Therefore, social network marketing is going to be more popular in every country, and it is not surprising that social networks are one of the most important tools to encourage the consumption of products.

Results
Measurement Models

     The reliability of the questionnaire was evaluated by Cronbach’s alpha, composite reliability, Dillon–Goldstein’s rho and by checking the first and second eigenvalues of the indicators’ correlation matrix (Table 2). Some researchers suggest 0.7 and above as the favorable point for Cronbach’s alpha [69,71–74] and DG rho [75]. As the value of these coefficients is higher than 0.7, it means that the reliability of the research is confirmed. The first eigenvalue should be much larger than 1, whereas the second eigenvalue should be smaller than 1 [75]. The outer loading values were above the 0.7 thresholds [76]. Meanwhile, the AVE (block communality) scores were above the threshold of 0.50 (Table 2), showing the internal consistency of the measurement model [77,78]. Figure 2 shows that all items have an acceptable outer loadings level based on the graphical outer loading figure (Plspm package with R).

     Discriminant validity was assessed at the construct level by the Heterotrait–Monotrait ratio (HTMT), as shown in Table 3. Values less than 0.9 are considered favorable for this index [79]. To assess the discriminant validity of items, cross-loadings were used by adopting the plspm package with R (see Figure 3) which show reliable results and confirmed the discriminant validity in the items level.

Abstract

Keywords

1. Introduction

2. Theoretical Background

3. Materials and Methods

4. Results

5. Discussion and Conclusions

6. Limitations and suggestions for future research

CRediT authorship contribution statement

Appendix A. Semi-structured interview guide (Ang et al., 2000; Baytiyeh, 2018; Kennett-Hensel et al., 2012; Priporas et al., 2017)

Appendix B

Appendix C

Appendix D

Appendix E

References

Vitae

Abstract

This study seeks to unravel the factors that have triggered changes in individuals’ engagement with online consumption during the COVID-19 crisis and investigate the influence of digital technologies on the retail ecosystem during the lockdowns, as seen through the eyes of consumers. In doing so, a qualitative empirical research approach was adopted, and data was collected via in-depth interviews with 35 respondents during the COVID-19 lockdown in China. The study has delineated a systematic mapping of the retail ecosystem’s reactions to the COVID-19 shock. Three overarching dimensions related to consumers’ online purchasing behaviors during the COVID-19 pandemic were identified: triggers of enhanced digital engagement, transformative capacity of digital technologies, and socio-economic adaptability during crises. The relevant themes underlying each aggregate dimension were further elaborated with evidence from the interviews. The study findings advance the extant literature on purchasing behavior and online retailing in times of crisis and offer important practical implications on improving crisis management capabilities of the retail ecosystem via digital technologies. As a final output, four propositions were extracted to serve for further research.

1. Introduction

In the last three decades, the technological developments of Web 2.0 and Web 3.0 have largely served as the driving forces for the Marketing 3.0 era of customization, and the digitalization age of Marketing 4.0, respectively (Erragcha & Romdhane, 2014; Shan et al., 2020). Information and communication technologies (ICTs), online marketing platforms and sophisticated digital devices have advanced exponentially, supporting the growth of various economic sectors (Zhu, 2021). Specifically, in the retail sector, various digital technologies support multichannel strategies or even an omni-channel approach, which offer consumers a range of alternatives in purchasing goods and services (Jin & Shin, 2020). Mobile devices, mobile apps, augmented reality and virtual reality applications, and various types of bots have already been in service instead of or combined with traditional human-to-human interactions – in either physical, online or hybrid offline/online settings – to serve customers’ needs and retailers’ goals (Hu & Tracogna, 2020; Verhoef et al., 2015).

The digital transformation of the retail sector has emerged through the natural evolution of digital technologies’ implementation, so retail organizations and individuals would facilitate their access to world markets, offering improved serviceability, and building competitive advantages (Altintas¸ et al., 2020). This set of retail actors comprise a generic retail ecosystem, who interchange goods and services for money and data, contributing to economic value streams. These actors can be branch retailers, online retailers, multi-channel retailers, IT-solution providers, service providers, store equipment providers, producers, data suppliers, logistics firms, and consumers (Bottcher et al., 2021 ¨ ).