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In this study, the service quality of an automobile authorized service center was investigated based on the European Customer Satisfaction Index (ECSI) model. The ECSI model includes image, customer expectations, perceived quality, perceived value, customer satisfaction, customer complaints and customer loyalty.

In the study, an attempt was made to improve the ESCI model by adding the trust factor as a moderating variable. After an extensive literature review, measurement questions were developed to best represent the factors in the research model. Partial least squares structural equation modeling (PLS-SEM) was used to test the fit of the research model and test the hypotheses.

As a result of the analysis, only one of the 13 hypotheses tested was not supported. According to the results of hypothesis testing, the highest effect was found in the relationship between customer satisfaction customer complaints, customer expectations and perceived quality. In addition, customer expectations affect customer satisfaction indirectly rather than directly. In this case, customer expectations, perceived value and perceived quality influence customer satisfaction.

The customer satisfaction quality index score of the authorized automobile service whose service quality was measured was calculated as 72.75. Although customers were generally satisfied with the authorized service, their expectations were not fully met.

In the study, an attempt was made to improve the ECSI model by adding a trust factor. Trust, which was added to the model as a moderator variable, fit the model. As a result, it was revealed that trust has an increasing regulatory effect on the relationship between perceived quality and customer satisfaction.

This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

New service businesses carry opportunities for industrial companies. The different cost management and management control implications of those service businesses deserve attention, which is a widely under-researched area in management accounting and control literature. Digital twins could hold potential in unveiling and supporting those new service business opportunities, as a unique approach of this paper. Thus, the purpose of this paper is to examine the possibility and potential for creating a digital twin of a service, especially to unveil the management accounting and control implications of the digital twin in developing new service businesses.

This paper investigates the potential of a digital twin in unveiling cost and control implications of new service businesses by examining the characteristics of a digital twin in the service business development context. The paper use an in-depth interventionist case study, where the designed animations illustrate the possibilities of a digital twin of a service. The animations showing the service process characteristics were first used as a communication tool and eventually those animations were actively used in customer cases for different purposes. This motivated the idea for examining the implications of such animations representing a digital twin of a service.

The paper provides empirical insights regarding the potential for developing and using a digital twin of a service for different cost management and management control purposes. The digital twin of a service may include all main details of a new service offering, simulating the functionality of a service, hence making the performance and the implications of the new service concept clear for all the stakeholders. The digital twin of the service enables defining the processes, setting targets and helps communication about the value generation. Thus, they represent a significant toolkit for the management accounting and control function of the manufacturers.

This paper is among the first attempts to understand the digital twin of the service. The paper is unique in providing financial and control implications of digital twins also in the context of service business development. The in-depth interventionist approach enabled an exceptional exploration process on the subject. The article paves the way toward further research on managing the digital twins of services in the future.

This paper aims to discuss the firm productivity premium for servitized firms. It discusses servitization across the product value chain and estimates the effects of the range and extent of servitization on productivity premium in manufacturing firms.

This paper develops a conceptual framework and tests the hypotheses on the effects of servitization on productivity premium using linear regression models with a sample of 20,837 Russian manufacturing firms gathered from the Ruslana Bureau van Dijk database and the Russian customs service.

Servitized firms exhibit higher total factor productivity and labor productivity. The labor productivity premium increases with the number of services offered. However, the impact of services on productivity varies along the product value chain: postmanufacturing and postsales services enhance productivity premium, while manufacturing and back-office services diminish them. The effect of establishment services remains ambiguous.

This paper offers an analytical framework for firms to assess their servitization strategies. These strategies should be gradual, focused on enhancing firm efficiency rather than being an end goal. Firms should initiate the process by introducing services at the postproduction and postsales stages of the product creation chain to achieve productivity premium.

The paper extends the evidence on firm-level productivity drivers and contributes to the servitization theory. A servitization strategy should be portfolio-based, considering both the potential gains and losses in productivity resulting from the implementation of specific services.

This empirical study aims to examine luxury fashion retailers' localised multiple channel distribution strategies in China.

Through case studies of 15 participating retailers, qualitative data were collected from 33 semi-structured interviews.

Strong impacts of internationalisation strategies, distribution strategies and channel length towards multiple channel retailing are revealed. Multi-channel retailing is widely employed by firms who have entered China and further developed their businesses through local partnerships and adopted a selective distribution strategy via relatively longer channels. Omni-channel retailing is only suitable for the few retailers using an exclusive distribution strategy through direct marketing and wholly owned customer relationship management. As a dynamic transformation from multi- to omni-channel retailing, cross-channel retailing is adopted by those who are withdrawing from local partnerships and shifting to wholly owned expansions and operations in host markets.

The results are potentially challenged by relatively small sample size.

Practitioners are suggested to adapt multiple channel retailing to their international expansion strategies, distribution strategies and channel length in the host markets.

This paper contributes to the literature in both multiple channel retailing and international retailing by offering insights into the motives, development patterns and suitability of multiple channel retailing in the international retail marketing context.

Warranty-based big data analysis has attracted a great deal of attention because of its key capabilities and role in improving product quality while minimizing costs. Information and details about particular parts (components) repair and replacement during the warranty term, usually stored in the after-sales service database, can be used to solve problems in a variety of sectors. Due to the small number of studies related to the complete analysis of parts failure patterns in the automotive industry in the literature, this paper focuses on discovering and assessing the impact of lesser-studied factors on the failure of auto parts in the warranty period from the after-sales data of an automotive manufacturer.

The interconnected method used in this study for analyzing failure patterns is formed by combining association rules (AR) mining and Bayesian networks (BNs).

This research utilized AR analysis to extract valuable information from warranty data, exploring the relationship between component failure, time and location. Additionally, BNs were employed to investigate other potential factors influencing component failure, which could not be identified using Association Rules alone. This approach provided a more comprehensive evaluation of the data and valuable insights for decision-making in relevant industries.

This study's findings are believed to be practical in achieving a better dissection and providing a comprehensive package that can be utilized to increase component quality and overcome cross-sectional solutions. The integration of these methods allowed for a wider exploration of potential factors influencing component failure, enhancing the validity and depth of the research findings.

Refractory materials are now used in all major industries that demand high-temperature resistance, including petrochemicals, steel, cement and aviation. Businesses must decrease operating costs, enhance product technology, sell well and manage corporate risks in decision-making, notably supplier selection, to be more competitive. The study aims to determine the key criteria and factors of supplier selection and to evaluate the importance of the key factor of the supplier selection criteria for the refractory materials manufacturers in Taiwan.

Analytical hierarchy process (AHP) is used to rank these factors for the decision maker. The AHP method is suitable for verifying refractory supplier selection criteria and providing references. The weighted loss scores for each supplier are then determined using the relative importance as the weights. Supplier selection criteria are ranked using their aggregate weighted loss scores. The provider with the lowest loss score should be chosen.

Product quality is the most significant of the five criteria: product quality, production technology, logistics capacity, service capability and supplier background. Professionalism is the most significant aspect of product quality, whereas equipment and capacity are vital in manufacturing techniques. The studies also show that the delivery rate is essential for logistics and service capabilities.

This research has important implications for refractory suppliers in promptly fine-tuning the production and service to enhance customer satisfaction, which is key to business sustainability.

The application of an AHP technique to a real-world industrial issue is what makes this research unique. This research addressed one of the most critical topics in supply chain operations by offering better judgement for supplier selection via the use of suitable quantitative methodologies.

Webrooming (i.e. searching information online and making the final purchase in a physical store) has become a popular shopping practice, but remains insufficiently studied. To address this, a research framework encompassing online and offline channel attributes (i.e. online review diagnosticity, online search convenience, expected price loss, offline purchase effort and offline after-sales service convenience), consumer traits (i.e. anticipated regret) and shopping experience (i.e. smart-shopping perception) as determinants of webrooming continuance intention is proposed.

The proposed model was validated by conducting a questionnaire-based survey that yielded 354 useable responses. The data was subjected to partial least squares structural equation modelling and importance-performance map analysis.

According to the obtained results, online review diagnosticity, offline after-sales service convenience and anticipated regret are the vital antecedents of webrooming continuance intention, while smart-shopping perception acts as the mediator.

The current study adds significantly to the body of knowledge about webrooming by validating the inter-relationships between online review diagnosticity, after-sales service convenience, anticipated regret, smart-shopping perception and webrooming continuance intention.

Small retail stores in the luxury market face significant challenges due to fluctuations in market demand. This task turns challenging as it requires effectively coordinating and translating customer needs into specific requirements that align with retail goals and available resources. However, limited empirical research exists investigating how managers can address service value and quality attributes in small retail stores. This article aims to bridge this gap by investigating the role of quality function deployment (QFD) in improving market and quality requirements management in small retail stores.

Based on the case study, a customer survey was initially conducted to gather information on critical characteristics valued in the luxury retail segment. QFD was used to assist the company in identifying and prioritizing key quality attributes to meet customer requirements effectively.

The findings demonstrate that implementing QFD in small luxury retail stores empowers managers to identify previously neglected product and service quality aspects. The article shows that QFD informs organizational adaptations that align with the demands of the retail market, leading to an improved ability to meet customer expectations and enhance customer value through the development of enhanced products and services. The study showcases the efficacy of the tested methodology in effectively capturing and prioritizing both tangible and intangible customer needs in retail.

Findings offer valuable insights to retail managers of small luxury stores, providing actionable market-oriented strategies. By implementing the recommended practices, managers can improve the store’s competitiveness and better cater to the customer base.

This study contributes to bridging persistent knowledge gaps by addressing the unique context of small luxury retail stores and introducing the application of QFD in this setting. The insights gained from this research are relevant to both retailing and quality management literature. Considering the growing prevalence of transformations in the retail industry, the study provides practical implications for retail managers in effectively navigating these changes.

In developing countries such as India, start-ups play an essential role in “industrial output,” “Gross Domestic Product ” and “employment creation.” Evidence suggests that pandemics have risen over the last century due to rising global travel and assimilation, urbanization, alterations in land use, and significantly larger exploitation of the natural environment. These trends are likely to continue and intensify. These pandemic episodes affect businesses, especially start-ups. Supplier selection is among the vital critical elements that start-ups must include in start-ups' strategy procedures during the pandemic episodes. This study's focus is to “identify,” “analyze,” and “categorize” the factors affecting supplier selection in start-ups during frequent pandemic episodes like coronavirus disease 2019 (COVID-19).

Through “literature review” and “experts' opinion” from various start-ups in India, ten affecting factors were identified. Total Interpretative Structural Modeling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) were employed to analyze the interrelationship among the factors affecting the supplier selection on start-ups during frequent pandemic episodes, and these factors were ranked as “autonomous,” “independent,” “linkage,” and “dependent” factors.

The findings show that “performance history,” “service levels,” “technical capability,” and “financial stability” are the most critical factors affecting the supplier selection on start-ups during frequent pandemic episodes. The next importance should be safety and environmental concern” and “quality.”

The factors affecting supplier selection on start-ups during frequent pandemic episodes are the current focus of this study. This study is mainly performed on Indian start-ups and can be extended to other countries.

The start-ups can rely on this study to clearly understand the factors affecting the supplier selection on start-ups during frequent pandemic episodes.

There is no research regarding factors affecting supplier selection on start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to supplier selection in start-ups. This gap inspired the present study, which employs the “Total Interpretive Structural Modeling (TISM)” technique to uncover supplier selection determinants and investigate hierarchical interconnections among factors influencing/affecting supplier selection in start-ups during frequent pandemic episodes.