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In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.

This study aims to highlight the impacts of a rapidly growing automobile industry on the environment and how implementation of Circular Economy (CE) principles and strategies can help us in improving its sustainability without compromising on our existing economic models.

Increase in spending capacity, improvements in technology and decrease in the prices have catapulted automobile demand over the last few decades. Harmful emissions and waste generation during the entire life cycle of these complex machines need to be addressed in an urgent manner globally. Implementation of CE principles and strategies which are based on promoting a pivotal balance between environment, economy and the society can lead to minimize economic and environmental impact leading to better results for all the stakeholders.

Carbon footprint or environmental emissions during different stages of an automobile life cycle can be minimized using CE principles and strategies without compromising on the existing economic models. Government legislation and keen participation of Original Equipment Manufacturers (OEMs) and automobile manufacturers can drive the automobile industry toward sustainability despite growing consumption.

The literature review has been done with a fresh perspective to combine environmental sustainability with CE. This is a literature review of prior work done in this domain to explore the possibility of further intervention in this domain.

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

This study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.

Based on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.

The results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.

The hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.

This study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.

The COVID-19 outbreak disrupted the business environment and severely affected the morale and performance of the employees. Further, the Indian automobile industry witnessed major setbacks and drastically impacted sector in COVID-19. Talent agility is an emerging concept in the field of HRM that will foster innovations and productivity in the automobile industry. Thus, this study aims to explore the barriers to building in-house agile talents in the Indian automobile industry in the new normal.

The barriers of talent agility were identified through a literature review and validated through experts’ opinions. This study used a hybrid approach, which combines Interpretive Structural Modelling-Polarity (ISM-P) and decision-making trial and evaluation laboratory (DEMATEL) to develop a hierarchical structural model of the barriers, followed by classification into cause and effect groups.

The result of the multi-method approach identified that shortage of skills and competencies, lack of IT infrastructure, lack of ambidextrous leaders, lack of smart HRM technologies and practices, lack of attractive reward system/career management, poor advanced T&D, poor industry, institute interface and financial constraints are the critical barriers.

It can provide a strategic roadmap for automobile manufacturers to promote talent agility in the current wave of digitalization (Industry 4.0). This study can help the managers to address and overcome the barrier and hurdles in building talent agility.

This study is unique in that it addresses the contemporary issues related to talent agility in the context of the Indian automobile industry in the current rapidly changing environment. This study developed a holistic integrated ISM(P)-DEMATEL hierarchical framework on the barriers of talent agility indicating inner dependency weights, i.e., the strength of interrelationship between the barriers.

The purpose of this study is to understand how the degree of congruence between buyers’ and sellers’ intentions to negotiate impacts buyers’ postpurchase emotions and attitudes. In addition, the study examines whether buyers’ self-confidence and negotiation expertise can increase buyers’ perceptions of control and regret, as well as buyers’ postpurchase satisfaction and enjoyment with the purchase. Traditionally, marketplace exchanges have been classified as either fixed price or negotiated. The present research treats marketplace exchanges along a continuum of intention congruence to test the relationships between intention congruence and outcome variables of control, regret, satisfaction and enjoyment with the purchase.

The authors studied the perceived difference between buyers' and sellers' intentions to negotiate and how the difference impacts buyers' postpurchase attitudinal and emotional outcomes. A mail survey of automobile buyers resulted in a sample of 291 respondents. An automobile is a significant and irreversible purchase for a buyer. Thus, automobile markets often host transactions that evoke dissonance and regret for buyers if things go awry. In addition, buyers and sellers vary considerably in their desire to negotiate, thus reflecting a range of intention congruence in negotiation. Therefore, a survey of automobile buyers was considered appropriate for testing the effects of intention congruence on buyers’ postpurchase outcomes.

Results indicate that when buyers are willing to negotiate but sellers do not reciprocate equally, buyers feel less in control of a transaction. Contrarily, buyers experienced greater control and lesser regret when buyers’ perceptions of sellers’ intention to negotiate exceeded buyers’ own intentions to negotiate. Results also suggest that when buyers’ intentions to negotiate were congruent with buyers’ perception of sellers’ intention to negotiate, greater dyadic levels of negotiation marginally lowered buyers’ perceived regret. Overall, an intention-congruence perspective adds to the current understanding of negotiated exchanges and is a meaningful approach for improving postpurchase outcomes for buyers.

The study used only the consumers’ perspective of negotiation. Although this is supported by studies in power and dependence because the consumers’ perspective is valuable and valid, a true dyadic measurement of the negotiation process can only be obtained if the sellers’ view is also incorporated. This remains a key limitation of this study.

The results suggest that sellers may be better off honoring buyers’ intentions to negotiate. Intention incongruence negatively impacted buyer satisfaction when buyers perceived sellers to be less eager to negotiate. However, where sellers seem more eager to negotiate, incongruity favored buyers and positively impacted buyers’ postpurchase outcomes. Thus, for sellers, it is worthwhile to consider adding policies that honor negotiation.

Past research classifies marketplaces exchanges as either fixed price or negotiated. The present study uses intention congruence as a continuum between transaction partners. The intention congruence approach allows a closer examination of both the symmetry and strength of intentions to negotiate in a dyadic exchange. Given that markets are comprised of buyers and sellers who display considerable variability in intentions to negotiate, examining intention congruence allows for a more realistic study of negotiation behavior in business-to-consumer marketplaces.

The purpose of this paper is to take second-hand vehicles at judicial auctions in China as the primary research direction and to explore the impact of purchasing restriction policy and city size on the relationship between the appraisal price and transaction price of second-hand motor vehicles in the context of auto purchase restriction in China from a microscopic angle. It attempts to broaden the pricing ideas of judicial appraisal enterprises in providing appraisal prices of second-hand motor vehicles and to put forward suggestions for the optimization of appraisal prices and appraisal standards of judicial appraisal enterprises.

With the help of Python, this paper crawls 59,038 lines of valid data from three leading internet judicial auction platforms, namely “Ali Auction,” “China Beijing Equity Exchange” and “Gong Pai Wang,” as research samples. Besides, this paper forms a database containing judicial auction used car appraisal prices, transaction prices, motor vehicle purchase restrictions and whether the motor vehicle carries a license plate. By constructing a multiple regression model, the impact of automobile purchase restriction policy on the price of motor vehicles appraised by judicial appraisal enterprises is investigated.

With the help of the multivariate regression model, it found that under the same condition, the city where the auction took place implemented the automobile purchase restriction before the end of the auction. The court has specified that the buyer could directly obtain the license plate after the auction. The transaction price and the evaluation price ratio will be statistically larger, which proves that the license plate has an evident value in the transaction and is traded as subject matter by the residents, and consequently brings a higher premium to the price of automobile transaction in internet judicial auction. Meanwhile, the purchase restriction policy in the first-tier cities has resulted in a significant premium on automobile license plates, which is much higher than the automobile license plate premium level in non-first-tier cities under the same conditions.

Car ownership continues to rise with rapid economic development worldwide. Control the growth of car ownership, some countries and regions mainly restrict the issuance of motor vehicle license plates, which indirectly leads to vehicle license plate indicators becoming a scarce resource. National laws permit judicial auction as a means for the people's courts to settle creditors' claims in enforcement procedures of civil cases. In the judicial auction process, the People's Court introduces third-party evaluation enterprises to appraise, assess and audit the subject and obtain the appraisal price, which guides the bidding behavior of used car buyers and indirectly affects the transaction price of used cars.

As the only subject capable of assessing the value of used cars at judicial auctions, judicial appraisal enterprises have received widespread attention for their appraisal results. This paper researches this field by screening the factors affecting the ratio of motor vehicle transaction price to the appraised price. It also analyzes how the ratio of motor vehicle transaction price to appraised price is affected by motor vehicle purchase restrictions and the situation with license plates. This paper examines the existence of premiums for motor vehicle transactions with license plates, evaluates the purchase restrictions in cities with motor vehicle purchase restrictions and verifies that the premiums for motor vehicles at judicial auctions are affected by purchase restriction policies as well as the influence of city class. These studies have important implications for judicial appraisal enterprises to establish reasonable appraisal mechanisms and optimize appraisal prices. They also provide new ideas and methods for appraisal enterprises to assess the value of used vehicles at judicial auctions.

The current study builds on social identity theory and realistic conflict theory aims to identify the relationships amongst consumers' ethnocentrism, animosity, discomfort with differences – a factor of universal-diverse orientation (UDO) – and reluctance to purchase German (RELG) and French automobiles (RELF) in the Turkish automobile market which is dominated by foreign brands.

Empirical data were collected via face-to-face surveys from 400 respondents in the emerging market Turkey. Structural equation modelling was employed to examine the direct and indirect effects between the variables.

The main predictors of the RELG are consumer ethnocentrism, discomfort with differences and economic animosity towards Germany, respectively. Furthermore, RELF in the Turkish market is positively affected by consumer ethnocentrism, war animosity towards France and discomfort with differences, respectively. Discomfort with differences mediates the relationship between consumer ethnocentrism and RELG and RELF.

International collaborations with local manufacturers have huge strategic impacts when establishing reliable relationships with Turkish consumers. Foreign companies can initiate socially responsible projects that will relay the message of similarities between cultures to decrease perceived cultural differences. Highlighting the similarities of Turkish consumers with a foreign company in promotional campaigns will be much beneficial.

Despite there are many studies regarding antecedents and consequences of consumer ethnocentrism, extant research overlooks the effect of animosity on this concept. Additionally, studies examining UDO in the marketing literature are scarce. This paper integrates UDO, consumer ethnocentrism, animosity and reluctance to purchase foreign products in one study.

The United Nations Industrial Development Organization (UNIDO) (2017, pp. 14–15) identified that “industrialization is the seedbed for entrepreneurship, business investment, technological progress, the upgrading of skills, and the creation of decent jobs.” This placed studying different industrial sectors and their respective clusters, which are key drivers for economy, innovation, and knowledge creation (Slaper, Harmon, & Rubin, 2018), at the forefront of research. This chapter tackles the automobile industrial cluster in Egypt that possesses promising potential yet faces some challenges. It aims to provide an overview of the cluster, alongside underpinning its strengths and obstacles facing it. Moreover, the chapter displays the importance of the labor dimension in increasing the labor competitiveness of the cluster and showcases this through two cases of German automobile manufacturers that pioneered in venturing into the market through employing technical and vocational education and training. In conclusion, recommendations are provided to help in steering the cluster toward success.

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.