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The aim of this research is to propose a quantitative approach to evaluating the quality of services provided, helping organizations to make strategic decisions by better understanding the characteristics that satisfy consumers.

The approach was based on the integration of the Kano model with SERVQUAL, adapted by the satisfaction equations of Albuquerque et al. (2022) and fuzzy systems theory. Through this, it was possible to infer which attributes influence customer satisfaction, identifying the ranges of satisfaction and, with the help of fuzzy, reducing the imprecision of customer perceptions.

A total of 42% of the attributes were classified as unidimensional, with attribute 11 (Reliability) and attribute 9 (Courtesy) having the highest satisfaction values. Attractive attributes accounted for 38% of the sample, with attribute 29 (Variety of products) and attribute 7 (Location) having the greatest impact on satisfaction. On the other hand, attribute 30 (Order Delay) and attribute 31 (Waiting for payment) caused more dissatisfaction among consumers (ranges −0.6, −0.71, respectively). In addition, Variety of products was the most satisfactory, while Order Delay generated the most dissatisfaction among users.

The originality of this research lies in its contribution to organizations in relation to the services offered by investigating a gap in the studies that use the Kano model, integrated with SERVQUAL, which do not include reverse attributes in their equations and analyses. With the help of fuzzy sets, the subjectivity of the individual can be translated into data for greater clarity of information.

China’s healthcare system is being burdened by the increasing prevalence of chronic diseases. Therefore, this study investigated the health service requirements of mobile health applications (mHealth apps) users in Hangzhou, China. This study aimed to propose suggestions and theoretical references to improve mHealth apps and promote their development, thereby meeting public medical and health needs and creating an efficient medical service system.

We constructed a model of health service demands using a literature review, network survey, and semi-structured interviews. We analyzed the demand attributes using the Kano model and Better-Worse index and obtained the priority ranking of demands.

The results revealed 25 demand elements in four dimensions: must-be (M), one-dimensional (O), attractive (A), and indifferent (I) requirements. The findings suggest that mHealth app developers can optimize health services by categorizing and managing health services, focusing on middle-aged users, enhancing the professionalism of health service providers, and improving the feedback mechanism.

Studies on mHealth apps user demands, particularly on health service needs, remain scarce. This study employed a mixed-methods approach, integrating both qualitative and quantitative research techniques, to establish a priority ranking of user health service needs for mHealth apps. The study offers recommendations and theoretical references to optimize and improve mHealth app services.

1. Construct a better health service requirements model for mHealth app users.

2. Obtain the prioritization of demand elements in the model.

3. Propose some management suggestions to improve mHealth apps.

Construct a better health service requirements model for mHealth app users.

Obtain the prioritization of demand elements in the model.

Propose some management suggestions to improve mHealth apps.

The study aims to provide concrete service remediation and enhancement for LLM developers such as getting user forgiveness and breaking through perceived bottlenecks. It also aims to improve the efficiency of app users' usage decisions.

This paper takes the user reviews of the app stores in 21 countries and 10 languages as the research data, extracts the potential factors by LDA model, exploratively takes the misalignment between user ratings and textual emotions as user forgiveness and perceived bottleneck and uses the Word2vec-SVM model to analyze the sentiment. Finally, attributions are made based on empathy.

The results show that AI-based LLMs are more likely to cause bias in user ratings and textual content than regular APPs. Functional and economic remedies are effective in awakening empathy and forgiveness, while empathic remedies are effective in reducing perceived bottlenecks. Interestingly, empathetic users are “pickier”. Further social network analysis reveals that problem solving timeliness, software flexibility, model updating and special data (voice and image) analysis capabilities are beneficial in breaking perceived bottlenecks. Besides, heterogeneity analysis show that eastern users are more sensitive to the price factor and are more likely to generate forgiveness through economic remedy, and there is a dual interaction between basic attributes and extra boosts in the East and West.

The “gap” between negative (positive) user reviews and ratings, that is consumer forgiveness and perceived bottlenecks, is identified in unstructured text; the study finds that empathy helps to awaken user forgiveness and understanding, while it is limited to bottleneck breakthroughs; the dataset includes a wide range of countries and regions, findings are tested in a cross-language and cross-cultural perspective, which makes the study more robust, and the heterogeneity of users' cultural backgrounds is also analyzed.

Autonomous vehicles (AVs) have the potential to transform the infrastructure, mobility and social well-being paradigms in New Zealand (NZ) amid its unprecedented population and road safety challenges. But, public acceptance, co-evolution of regulations and AV technology based on interpersonal and institutional trust perspectives pose significant challenges. Previous theories and models need to be more comprehensive to address trust influencing autonomous driving (AD) factors in natural settings. Therefore, this study aims to find key AD factors corresponding to the chain of human-machine interaction (HMI) events happening in real time and formulate a guiding framework for the successful deployment of AVs in NZ.

This study utilized a comprehensive literature review complemented by an AV users’ study with 15 participants. AV driving sprints were conducted on low, medium and high-density roads in Auckland, followed by 15 ideation workshops to gather data about the users’ observations, feelings and attitudes towards the AVs during HMI.

This research study determined nine essential trust-influencing AD determinants in HMI and legal readiness domains. These AD determinants were analyzed, corresponding to eight AV events in three phases. Subsequently, a guiding framework was developed based on these factors, i.e. human-machine interaction autonomous driving events relationship identification framework (HMI-ADERIF) for the deployment of AVs in New Zealand.

This study was conducted only in specific Auckland areas.

This study is significant for advanced design research and provides valuable insights, guidelines and deployment pathways for designers, practitioners and regulators when developing HMI Systems for AD vehicles.

This study is the first-ever AV user study in New Zealand in live traffic conditions. This user study also claimed its novelty due to AV trials in congested and fast-moving traffic on the four-lane motorway in New Zealand. Previously, none of the studies conducted AV user study on SUV BMW vehicle and motorway in real-time traffic conditions; all operations were completely autonomous without any input from the driver. Thus, it explored the essential autonomous driving (AD) trust influencing variables in human factors and legal readiness domains. This research is also unique in identifying critical AD determinants that affect the user trust, acceptance and adoption of AVs in New Zealand by bridging the socio-technical gap with futuristic research insights.

This case study aims to simulate the learners’ thoughts about the earnest comprehension of sustainable brands with zero waste policy. It will further prompt them to anatomize the growth strategy of a sustainable brand, as it delineates the challenges faced by a woman ecopreneur. In response to these causative conundrums, the incumbent would be able to develop an understanding on the evolving landscape in context to the association between meeting consumer expectations, brand positioning and its channelization towards growth and revenue generation. Furthermore, the learners will be able to analyse the stages of product life cycle of a sustainable product and recommend an effective strategic plan to meet the consumer expectations and achieve desired growth by the application of Kano model.

Thenga was a home-grown brand from Kerala (God’s own country) founded by Maria Kuriakose, a native of Kerala in 2019. Unlike other brands, which were using coconut as a source of flesh, water and oil, Kuriakose came up with an idea of using the tossed shells of coconuts which eventually used to end up at landfills. These shells were crafted into aesthetics by the team of Thenga while adhering to the zero-waste policy. The brand gained momentum with the overwhelming positive response from the natives of Kerala and carved a way across the boundaries of Kerala, gradually reaching to every corner of India. Kuriakose thought of scaling the brand in the international boundaries as well. Within no time, the brand was a success. However, over the time, the brand was confronted with two broad dilemmas. First, non-uniformity in the sizes of the products, especially in bulk orders where maintaining uniformity was essential. The customers complained that there was no uniformity in the size of the products because for gifting purposes, they wanted all the products to look alike. And second, selecting the stringent quality shells because the ones exposed to sun for a very long time were not ideal for crafting the products due to the cracking of the shells, thereby affecting their durability. It became difficult addressing to these complex issues because the shells were nature’s creations. These issues were very different from the managerial dilemmas. Would the perspectives of management provide a solution? Kuriakose had to find a way out in the long term for the survival of the brand especially during its growth phase.

The case study is relevant for students in disciplines of entrepreneurship, green marketing, brand management, corporate social responsibility and strategy. It is designed for advanced MBA/PGDM and capstone courses. The case study also addresses the elements of customers’ perceptions towards innovative products and can be used as an addition for marketing courses dealing with strategies to improve the awareness and adoption of sustainable products.

Teaching notes are available for educators only.

CSS 4: Environmental management.

Housing is one of the basic necessities of humankind for survival and purchasing a home is often a substantial milestone. Individuals exhibit complex behaviour influenced by various factors while making decisions related to the purchase of residential properties. While most of the earlier studies have focused on understanding the purchasing behaviour of home buyers’ in developed countries, the research is limited on this topic in developing countries such as India. The booming information technology industry has rapidly increased the demand for residential properties among the migrant population in Bengaluru, India’s largest technology hub. Real estate developers strive to meet the requirements of prospective customers through innovative ways but face challenges in a competitive market.

It is essential to understand the factors influencing home buyers’ purchase attitudes for increasing property sales. However, a lack of research on this subject is identified in the emerging city of Bengaluru. This study aims to analyse the determinants of home buying decisions for potential investors in Bengaluru through structural equation modelling to provide insights for the real estate industry to construct houses as per their customers’ needs.

It was found that housing amenities, financial aspects, location conveniences and marketing services significantly influenced home buyers’ purchase decisions, whereas housing features do not.

The findings of this study offer valuable insights for governmental bodies to implement appropriate policies and for builders to design properties with features that cater to the target population, thereby promoting sustainable growth in the real estate industry.

Smart libraries are the result of the application of smart technologies in the era of digital intelligence. The establishment and improvement of its service evaluation system serve as indicators for evaluating the growth of smart libraries.

This study introduces and improves the capability maturity model (CMM), creatively constructs a service maturity model specifically designed for smart libraries and combines the Delphi method with the analytic hierarchy process (AHP) to establish a service maturity evaluation system for smart libraries while calculating indicator weights. Finally, two representative smart libraries are selected as case studies, and an empirical application is conducted using the fuzzy comprehensive evaluation method.

The empirical study shows that the developed smart libraries service maturity evaluation system holds significant theoretical and practical value in evaluating smart libraries.

Enhances the CMM and creatively constructs a service maturity model for smart libraries. Combines the Delphi method with AHP to establish a service maturity evaluation system while calculating indicator weights. Uses a fuzzy comprehensive evaluation method to evaluate two representative smart libraries. Demonstrates that the smart library services maturity evaluation system holds significant theoretical and practical value.

This study addresses the gap in understanding text analytics within the service domain, focusing on new service development to provide insights into key research themes and trends in text analytics approaches to service development. It explores the benefits and challenges of implementing these approaches and identifies potential research opportunities for future service development. Importantly, this study offers insights to assist service providers to make data-driven decisions for developing new services and optimising existing ones.

This research introduces the hybrid thematic analysis with a systematic literature review (SLR-TA). It delves into the various aspects of text analytics in service development by analysing 124 research papers published from 2012 to 2023. This approach not only identifies key practical applications but also evaluates the benefits and difficulties of applying text analytics in this domain, thereby ensuring the reliability and validity of the findings.

The study highlights an increasing focus on text analytics within the service industry over the examined period. Using the SLR-TA approach, it identifies eight themes in previous studies and finds that “Service Quality” had the most research interest, comprising 42% of studies, while there was less emphasis on designing new services. The study categorises research into four types: Case, Concept, Tools and Implementation, with case studies comprising 68% of the total.

This study is groundbreaking in conducting a thorough and systematic analysis of a broad collection of articles. It provides a comprehensive view of text analytics approaches in the service sector, particularly in developing new services and service innovation. This study lays out distinct guidelines for future research and offers valuable insights to foster research recommendations.

Global value chains (GVCs) are facing unprecedented pressures arising from structural changes in the global economy and exogenous shocks including military conflicts and the aftermath of COVID-19. Considering the importance of value chain analysis in the current environment, the purpose of the study is to provide an up-to-date overarching global value chain literature review study that offers suggestions for research and practice to ensure resilient value and supply chains.

The authors provide a comprehensive review of literature of the value chain, commodity chain and production network research based on a systems overview of 5,628 publications to identify the extent of research on vulnerabilities and resilience of value chains globally and gaps therein. To provide the systems overview, the authors use scientometric content co-occurrence analysis methods to analyze and identify gaps within the existing literature.

Based on this overarching review of the literature, the authors identify gaps in the literature primarily related to the issue of unpreparedness of value chains to exogenous shocks. The authors suggest future research directions and propose an integrative model along with recommendations for restructuring value chains for resilience amidst exogenous shocks.

This study carries out an overarching study of interdisciplinary GVC literature in the age of geopolitical and societal challenges and is thus able to offer holistic insights and propositions for future research.

This study aims to use the voice of the customer (VoC) strategy to collect user-generated content (UGC) compare customer expectations with reality, make the necessary improvements for the business and create personalized strategies for each customer to maximize revenue, focus on hospitality industry in Vietnam market.

This study proposes a synthesis of techniques for a deep understanding of the VoC based on online reviews in the hospitality industry. First, 409,054 comments were collected from websites in the hospitality sector. Second, the data will be organized, stored, cleaned, analyzed and evaluated. Next, research using business intelligence (BI) solutions integrating three models, including net promoter score (NPS), graph model and latent Dirichlet allocation (LDA), based on natural language processing (NLP) technique, experiment on Vietnamese and English data to explore the multidimensional voice of customer’s row. Finally, a dashboard system will be implemented to visualize analysis results and recommendations on marketing strategies to improve product and service quality.

Experimental results allow analysts and managers to “listen to the customer’s voice” accurately and effectively, identify relationships between entities, topics of discussion in favor of positive and negative trends.

The novelty in this study is the integration of three models, including NPS, graph model and LDA. These models are combined based on the BI solution and NLP technique. The study also conducted experiments on both Vietnamese and English languages, which ensures more effective practical application.