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This study proposes a new framework for business process improvement (BPI) by identifying areas of improvement based on customer complaints.

The proposed framework comprises several stages. The first stage captures the voice of customer (VoC) in the form of customer complaints. The complaints are processed using text mining and sentiment analysis. Negative sentiments indicate areas for improvement by matching words with SERVQUAL dimensions. The FMEA method is used to identify business processes that need to be improved.

The opposing quality dimensions of SERVQUAL can be incorporated into a database for later identifying consumer complaints. FMEA can be used to identify potential failures in aspects that correspond to consumer complaints; therefore, improvement areas can be identified. The proposed framework, applied to a garment manufacturer, shows that the SERVQUAL dimensions, which were originally intended for service companies, can be adapted to manage customer complaints to support BPI in manufacturing companies.

The framework can be used by either the manufacturing or service industries to handle customer complaints and use the complaint analysis results to identify improvement areas to avoid the same complaints occurring in the future.

In this study, the construction of a database based on the SERVQUAL dimension to match sentiment results, where negative sentiment indicates improvement, and the use of FMEA to indicate specific business processes that should be improved is novel and has not yet been proposed by previous studies.

The continuous evolution of the UAE necessitates adapting to the dynamic nature of facilities management (FM) and construction sectors. Therefore, this study explores the current asset maintenance management (AMM) practices and FM teams' roles in the early stages of planning.

Twenty semi-structured interviews with 13 FM experts and 7 construction professionals (consultants, managers, directors, engineers) in the UAE were conducted. Data were analyzed thematically and validated by the triangulation method.

The study unveiled a disconnection between the FM and construction sectors in the UAE, unlike the global markets. Interviewees highlighted several areas that could benefit from improved collaboration between these sectors, including data transfer, space planning, design review, sustainability practices and energy savings, maintainability, defects liability period (DLP) and lifecycle cost (LCC) and budget estimation and feasibility. Additionally, the most frequently reported barriers to the collaborative approach were the immaturity of FM in comparison to the construction sector (60%) and the lack of awareness of technology (50%). Raising awareness on the importance of early FM involvement was voted the most as a solution to the barriers identified (70%). Interviewees further emphasized the crucial role of building information modeling (BIM) in fostering this collaboration.

The study’s originality lies in its focus on the UAE’s regional context and the use of qualitative insights from experts to understand the nuanced interactions between FM and construction, providing an in-depth analysis of local collaborative practices.

This paper aims to provide insights into service innovation (SI) during the COVID-19 crisis and its potential impact on tourism development in the medium-to-long term. The pandemic had a devastating effect on the industry, requiring immediate mitigation. It is yet to fully establish the impact of SI in the face of the COVID-19 volatility, uncertainty, complexity and ambiguity (VUCA). This study discusses the potential link between SI and COVID-19 crisis mitigation and offers recommendations for tourism recovery.

This paper synthesizes empirical evidence on post-crisis tourism SI using a theory-based general literature review approach.

COVID-19 crisis spun various forms of SI, which emerged as a conventional solution to crisis prevention, encompassing the management of crisis-time competitiveness, revenue deficits and risk perception. However, resistance to innovative services is linked to situational conditions.

COVID-19 is an unprecedented crisis. Therefore, this study serves as a primer for further inquiry into SI. For instance, areas such as governance in tourism innovation and consumers' inclination toward innovation-driven services are underexplored.

SI acts as a situational facilitator, but its characteristics can impede or facilitate adoption. Moreover, the irrelevance of innovations in some environments is evidenced. Thus, practitioners must adopt a responsive learning approach in SI adoption. To mitigate the COVID-19 impacts, reconfiguration in SI, recovery marketing strategy, knowledge gap and governance will be critical interventions.

This paper is one of the first comprehensive discussions on the potential role of SI in mitigating the impact of COVID-19 on the THI.

As innovative household products, social home robots have a significant impact on the interactive consumer experience. However, prior research on consumer intentions to use such robots has rarely considered the configuration perspective. The present study examines how consumers balance the key benefits and risks created by these robots and explores how key influential factors jointly influence usage intention from a configuration perspective.

We adopted a hybrid research design. In Study 1, a thematic analysis was conducted to derive a conceptual framework reflecting the interplay of key factors influencing usage intention. In Study 2, a fuzzy set qualitative comparative analysis (fsQCA) was applied to reveal how these factors jointly shape usage intention.

Equifinal configurations of antecedent conditions (i.e. emotional and instrumental support beliefs, concerns about informational and relational privacy risks, self-construal and anthropomorphic design) led to usage intention. Additionally, four distinct benefit-risk trade-off patterns emerged across individuals.

This study highlights the need to examine robot adoption in interactive marketing, particularly in the service domain. It has implications in the context of commercializing social home robots, emphasizing the potential of leveraging social home robots to enhance interactive consumer experiences and foster close connections with consumers.

We developed a neoconfigurational model to obtain a comprehensive understanding of social home robot acceptance in domestic settings, highlighting its implications for consumer–robot interactions and advancing research in interactive marketing.

Employing the extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, this study examines the potential differences between two groups of hotel guests – business and leisure travelers – in terms of factors influencing their intention to purchase hotel products on Douyin (TikTok) in China.

Data gathered from 700 Chinese hotel guests was analyzed using partial least squares-structural equation modeling (PLS-SEM) and multigroup analysis (MGA).

The MGA results reveal that three newly added variables – personalization, perceived interactivity and perceived creativity – significantly influence the purchase intention of leisure travelers but not business travelers. Regarding the conventional UTAUT2 variables, leisure travelers are more influenced by hedonic motivation and price value in their purchasing decisions. In contrast, performance expectancy and effort expectancy have a greater impact on the decision-making process of business travelers than their leisure counterparts.

Theoretically, this paper is among the first to explore traveler types as moderators in the purchase of hotel products on Douyin. Practically, the findings offer valuable guidance for hotel marketers aiming to leverage Douyin to promote hotel products to these two different traveler segments.

Instead of using “one-size-fits-all” strategies, hotel managers should design marketing strategies that address the diverse needs of business and leisure travelers on Douyin. By implementing this strategy, they can effectively attract target customers and, in turn, increase hotel revenue.

This study expands the UTAUT2 framework and contributes to the scarce knowledge about the differences between business and leisure travelers regarding the relative importance of factors that influence their purchase intention for hotel products on Douyin among business and leisure travelers.

This study aims to assess how ethical sales behaviour affects switching costs typology, mediated by trust and moderated by brand affiliation, monthly contributions and the number of dependent beneficiaries in medical schemes in South Africa.

A quantitative study targeted a non-probability judgement sample of 250 main members of medical schemes, elicited near health-care facilities in South Africa’s Gauteng province. Data was collected in a face-to-face survey and analysed using structural equation modelling on AMOS version 29 and PROCESS procedure for Statistical Package of Social Science release 2.041.

The results show that ethical sales behaviour negatively affects trust and positively affects evaluation, monetary and personal relational loss costs. Trust positively affects personal relational loss costs, economic risk, evaluation, monetary and benefit loss costs. Moreover, trust mediates the effect of ethical sales behaviour on evaluation, monetary and personal relational loss costs. Finally, the number of dependent beneficiaries, monthly contributions and brand affiliation significantly moderate these interactions.

The paper validates the application of commitment-to-trust theory in mediating how the effects of the general theory of marketing ethics on switching costs typology differ according to the number of dependent beneficiaries, monthly contributions and brand affiliation with medical schemes.

The study aims to predict the drivers of green purchase in extended theory of planned behaviour (TPB) by investigating direct and indirect role of consumers' attitude toward green purchase along with moderating effects of green trust and willingness to pay on purchase behaviour in an emerging market.

A total of 417 useable responses were recorded from three different states of north India to resolve the issues related to demographic diversity in country by using a structured questionnaire. Structural equation modelling, mediation and moderation analyses were used to investigate the hypothesised relationships.

The research unveiled that environmental concern, subjective norm have significant direct and indirect influence on green purchase intention via attitude. Furthermore, this study also elucidates that green trust significantly moderates attitude–behaviour, and intention–behaviour relationships, whereas willingness to pay does not significantly moderate these relationships in proposed model.

This study provides interesting insights regarding consumers of emerging market toward green purchase. These insights are useful for marketers to design more focused strategies for enhancing the consumers' preferences for green products and promotion of pro-environmental behaviour in emerging markets.

The novel insights of this study are the mediating role of attitude in an emerging market in extended TPB model and exploration of the moderating role of green trust and willingness to pay premium to reduce the attitude–behaviour and intention–behaviour gaps for enhancing the consumers' preferences for green purchase.

In influencer advertising, followers engage in more frequent and timely interactions compared to nonfollowers, making them the primary audience for these advertisements. Building on this premise, this study aims to examine the impact of different influencer types, categorized by follower count, on the advertised brands.

The authors tested the hypotheses in four studies, including one secondary data analysis and three experiments.

Combining real-world data with a series of experiments, the authors show that the followers of mega-influencers (vs micro influencers) have a more positive response to the advertised brands, with more positive brand attitudes, greater purchase intentions and higher engagement. The authors call this the “mega-influencer follower effect.” It is driven by the sense of control. This effect only occurs among the followers and not nonfollowers. Moreover, the mega-influencer follower effect only existed in human influencers, not virtual influencers.

This study takes influencer followers as influencer advertising audiences and investigates the effect of influencer types (based on the number of followers) on the advertised brands; however, future research may investigate how consumers respond to brands in different categories endorsed by influencers.

The authors argue that influencer advertising audiences are more likely to be followers of the influencer. From this perspective, the results suggest that marketers should cooperate with mega-influencers.

Through emphasizing the value of followers rather than nonfollowers as audiences, this study expands the literature on influencer marketing and the explanatory mechanisms regarding which types of influencers are more effective.

Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. This study endeavors to systematically analyze the underlying mechanisms governing how negative reviews exert an influence on potential consumer decisions.

This paper constructs an “Aspect-based sentiment accumulation” index, a negative or positive affect load, reflecting the degree of consumer sentiment based on affect infusion model and aspect-based sentiment analysis. Initially, it verifies the causal relationship between aspect-based negative load and consumer decisions using ordinary least squares regression. Then, it analyzes the threshold effects of negative affect load on positive affect load and the threshold effects of positive affect load on negative affect load using a panel threshold regression model.

Aspect-based negative reviews significantly impact consumers’ decisions. Negative affect load and positive affect load exhibit threshold effects on each other, with threshold values varying according to the overall volume of reviews. As the total number of reviews increases, the impact of negative affect load diminishes. The threshold effects for positive affect load showed a predominantly U-shaped course of change. Hosts respond promptly and enthusiastically with detailed, lengthy text, which can aid in mitigating the impact of negative reviews.

The study extends the application of the affect infusion model and enriches the conditions for its theoretical scope. It addresses the research gap by focusing on the threshold effects of negative or positive review sentiment on decision-making in sharing accommodations.

This study explores how predictor variables (value congruence and customer–AI-assisted exchanges) lead tourism businesses to meet customer needs through contactless technology and enhance their willingness to pay more.

The research model was designed from the perspective of consumer-brand relationships and acceptance of AI device use. This study collected and analyzed 647 valid questionnaires using the structural equation modeling (SEM) approach.

The findings indicate that value congruence and customer-AI-assisted exchanges (CAIX) affect intimacy. Intimacy affects satisfaction and the willingness to pay more for contactless technological services. Moreover, brand trust and sensory brand experience play a role in moderating contactless technological services.

Effective interactions between customers and AI-assisted services significantly contribute to overall satisfaction. When AI systems can understand and respond appropriately to customer queries, needs, and preferences, they enhance customer experience and satisfaction levels, increasing overall customer satisfaction with AI services.