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This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.

While, supply chain resilience (SCRES) continues to be a dominant topic in both academic and business literature and has gained more attention recently, there is limited knowledge on SCRES capabilities specific to business functions. The purpose of this paper is to identify and investigate capabilities shared between supply, operations and logistics that are most important for SCRES.

To address this gap, the authors followed a multi-method research approach. First, the authors used the grounded theory method to generate a theoretical framework based on interviews with 51 managers from five companies in automotive SCs. Next, the authors empirically validated the framework using a survey of 340 SC professionals from the manufacturing industry.

Five significant capabilities emerged from the qualitative study; all were significant in empirical validation. This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES.

This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES. In addition, the findings of this research help managers better allocate resources among significant capabilities.

This paper aims to identify the basis of the technological anxiety phenomenon by defining the differences and similarities in terms of barriers of the implementation of Industry 4.0 technologies across industrial processing sector.

This paper presents a qualitative, exploratory research, and the authors apply the cross-case study method. The study is based on interviews with representatives of 11 medium-sized and large companies from industrial processing sector; specifically, the authors focus on three industries: automotive, food and furniture.

The research showed that there are similarities as well as differences in terms of identified barriers between individual industries. Taking into account the various dimensions of technological anxiety, similarities are visible, in particular, in the case of Internal processes and infrastructure and human resources, while in the other two dimensions, i.e. strategic planning and standards and security, differences between the sectors were noted.

The developed list of barriers can be a starting point for middle and senior managers of manufacturing companies to understand the sources of technological anxiety. The planning and introducing preventive and protective tools during Industry 4.0 implementation may reduce the occurrence of technological anxiety and thus ensure a smoother adoption of technologies 4.0, while respecting the organizational culture.

This work contributes to in-depth understanding of multifaced technological anxiety phenomenon. This paper classifies dimensions of existing barriers, increases the awareness on the difficulties during transformation process and, thus enables the improvement of the use of company’s internal potential.

The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).

To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.

The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).

This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.

This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.

Consumer perception of corporate brand equity has primarily focused on product brand dimensions, neglecting considerations at the firm analysis level. Assessing corporate brands requires different criteria relevant to the competitiveness of companies, such as their prominence, management and meeting society’s demands. In this sense, this study aims to develop and validate a scale of corporate brand equity founded on consumer perceptions, transcending industry boundaries and comparing its relationship with companies' market share.

The authors used an integrative approach to clarify the construct’s domain, building on previous measures. They took several steps to select appropriate items, refine the measure, validate it through reliability tests and convergent and discriminant analyses, test the validity of the second-order formative structure of corporate brand equity and assess associations between first-order factors, the second-order factor and market share.

The model identifies three first-order dimensions of corporate brands (presence, outstanding management and responsible) that shape the second-order factor (corporate brand equity). They are directly related, but not proportionally, to market share, contributing to the general and joint assessment of the company’s competitive performance considering the consumer.

To the best of the authors’ knowledge, this study is the first attempt to develop a comprehensive measurement model of corporate brand equity that considers the firm level of analysis, combines metrics from previous research on corporate brand evaluation criteria and includes consumer perceptions of the company’s competitiveness, unifying branding theory with the theory of the marketing firm.

Idea of circular economy defies the classical “make-use-dispose” approach of linear economic model. In the context of health-care industry, it relies heavily on the supply chain practices implemented by industry stakeholders. The purpose of this study is to explore such relationships, study their structure and put it across for attaining sustainability at large.

This study is an empirical research conducted on 145 health-care firms. The collected data is analysed to develop structural and measurement model. The five constructed hypotheses are examined and tested through structural equation modelling.

The study illustrates the latent relationships that exist among the stakeholders involvement, sustainable supply chain practices, sustainable performance and circular economy for health-care industry. It is found that the adoption of sustainable supply chain practices improves health-care performance, which, in turn, have positive influence on circular economy.

The structural and measurement model is developed in the context of circular health-care economy. It can be validated or improvised by conducting similar research in other industry using different methods. This research work fulfils the long existing gap in research by offering a linkage between various constructs to achieve health-care circular economy. Based on the research results, future researchers can build theories of circular economy and sustainability for health-care industry.

The study attempts to study the supply chain ways to achieve circular economy for Indian health-care sector. It considered latent relationships among the set of constructs, which are needed for theory building at later stage.

This study aims to investigate whether Industry 4.0 digital technologies can enhance the effects of lean production on social performance.

Survey data collected from China’s manufacturing industry are used to test research hypotheses.

The results reveal that the three dimensions of lean production (internal, customer and supplier) have a significant positive effect on social performance and that digital technology advancement (DTA) positively moderates these relationships. DTA adds only a marginal contribution to social performance.

This study addresses a new challenging question from manufacturing firms: how to integrate lean, technology and people? The empirical findings provide timely and insightful practical guidance for managers to better understand the role of digital transformation in the traditional lean context.

While digitalization is known to complement lean production, this study shows digitalization also complements the effects of lean production on social performance.

Acknowledging, on the one hand, the increasing fragility of supply chains and the number of risks involved in supply chain operations and, on the other hand, the role of small- and medium-sized enterprises (SMEs) in supply chains and the high exposure of these firms to risks of different types, this study aims to examine the relationship between supply chain risk management (SCRM) and innovation performance in SMEs. Furthermore, the impact of technological turbulence on this relationship was studied to take into account recent technological changes.

Structural equation modelling was carried out on a sample of Turkish SMEs to test the hypotheses developed.

The findings presented allow the authors to better understand the link between SCRM and innovation performance in SMEs. More precisely, empirical evidence is provided about the impact of SCRM components such as maturity and ability on innovation performance. Furthermore, the findings show the impact of technological turbulence on both SCRM and innovation performance.

By focusing on SCRM in SMEs, this paper contributes to the body of knowledge with regard to SCRM in general and with regard to SMEs in particular; research on the latter has only started recently. Moreover, by having studied SMEs from a developing country (other than China), this paper helps to develop a broader and more diverse perspective of SCRM.

This research work has developed an integrated fuzzy Delphi and neutrosophic best–worst framework for selecting the sustailient (sustainable and resilient) supplier for an additive manufacturing (AM)-enabled industry.

An integrated fuzzy Delphi method (FDM) and neutrosophic best–worst method (N-BWM) approach is developed. 34 supplier evaluation criteria falling under 4 groups, that is, traditional, sustainable, resilient, and AM specific, are identified and validated using the FDM. Afterward, the weights of each criterion are measured by N-BWM. Later on, the performance evaluation is carried out to determine the best-suited supplier. Finally, sensitivity analysis is performed to know the stability and robustness of the proposed framework.

The outcome indicates the high performance of the suggested decision-making framework. The analysis reveals that supplier 4 (S4) is selected as the most appropriate for a given firm based on the FDM and N-BWM method.

The applicability of this framework is demonstrated through an industrial case of a 3D-printed trinket manufacturer. The proposed research helps AM decision-makers better understand resiliency, sustainability, and AM-related attributes. With this, the practitioners working in AM business can prioritize the supplier selection criteria.

This is the primitive study to undertake the most critical aspect of supplier selection for AM-enabled firms. Apart from this, an integrated FDM-N-BWM framework is a novel contribution to the literature on supplier selection.

This paper aims to compare the wear behavior, surface roughness, friction coefficient and volume loss of high-velocity oxy-fuel (HVOF) sprayed WC–Co and WC–Cr₃C₂–Ni coatings on AISI 1095 steel with spraying times of 10 and 15 s.

In this study, the pin-on-disc testing technique was used to evaluate the wear characteristics at a speed of 0.24 m/s, load of 40 N and test time of 60 min under dry conditions at room temperature. The wear characteristics were examined and analyzed by scanning electron microscopy and energy dispersive X-ray spectroscopy. The surface roughness of a coated surface was measured, and microhardness measurements were performed on the cross-sectioned and polished surfaces of the coating.

Spraying time and powder material affected the hardness of HVOF coatings due to differences in the porosity of the coated layers. The average hardness of the WC–Cr₃C₂–Ni coating with a spaying time of 15 s was approximately 14% higher than that of the WC–Cr₃C₂–Ni coating with a spraying time of 10 s. Under an applied load of 40 N, the WC–Co coating with a spraying time of 15 s had the lowest variation in the friction coefficient compared with the other coatings. The WC–Co coating with a spraying time of 10 s had the lowest average and variation in volume loss compared to the other coatings. The WC–Cr₃C₂–Ni coating with a spraying time of 10 s exhibited the highest average volume loss. The wear features changed slightly with the spraying time owing to variations in the hardness and friction coefficient.

This study investigated tribological performance of WC–Co; WC-Cr₃C₂-Ni coatings with spraying times of 10 and 15 s using pin-on-disc tribometer by rotating the relatively soft pin (C45 steel) against hard coated substrate (disc).