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This study aims to set out to develop and validate a new instrument to measure the multi-dimensional nature of co-opetition in corporate responsibility and sustainability (CRS). It is anticipated that this instrument will prove useful to firms wanting to adopt measures that support relevant sustainability strategies.

The scale development concerns three separate components, namely, item generation through expert interviews; a pilot study conducted for scale purification; and a final study for scale confirmation and validation, respectively. The final study comprises 215 firms across 11 sectors in Australia that engage in co-opetitive alliances for CRS activities.

This study empirically validates the distinctiveness of three dimensions (commonality-driven, competition-driven and collaboration-driven) of co-opetition in relation to CRS resulting in a 15-item multi-dimensional scale. The three dimensions were found to be important aspects both in terms of scale validity and organisational consideration.

This study proposes a new research area regarding the proposed framework, as well as practical strategies for practitioners when considering co-opetition and their firm’s engagement in CRS activities.

Prior studies in similar areas have mainly comprised conceptual or qualitative approaches and do not tend to focus on all three aspects of co-opetition, corporate social responsibility and sustainability.

As an emerging technology, Radio Frequency IDentification (RFID) and blockchain have the potential to disrupt many areas of business and social structure. However, it is loaded with significant technical, social, legal, financial and ethical complications that bring difficulty in its widespread use within the public distribution system (PDS). This research aims to analyze the barriers to integrated RFID and blockchain adoption in developing countries' PDS. Furthermore, this study also aims to validate the proposed framework against the Indian PDS.

The proposed framework consists of 10 potential barriers to integrated RFID and blockchain adoption. To identify the barriers, this study referred to the extant literature followed by consultations with domain experts. This study prepared the DEMATEL-based questionnaires, collected the data from four domain experts and analyzed them using an integrated Grey-DEMATEL approach.

The obtained results provide a precise list of barriers and the correlations among them. From the results, it is concluded that the unavailability of a skilled workforce at affordable cost, lack of knowledge about privacy level and unclear return on investment and benefits are the most critical blockchain adoption barriers in the context of Indian PDS.

This research proposes a framework consisting of 10 integrated RFID and blockchain adoption barriers in relation to Indian PDS. It also proposes a method for analyzing causal interrelationships between the barriers while allowing for data input from domain experts. Consequently, the framework is capable of coping with experts' biases and data scarcity.

This study aims to explore the factors influencing the bottom of the pyramid (BOP) consumers’ adoption and usage intention towards mobile payment (m-payment) to achieve financial inclusion and sustainable development goals.

A qualitative research design is used to explore the enablers and inhibitors that influence BOP consumers’ m-payment adoption and usage intention. To collect the qualitative responses, semi-structured in-depth interviews with BOP respondents were conducted. The thematic analysis using the text mining technique will be used to analyse qualitative data for exploring the predominant factors affecting m-payment adoption intention and usage.

The results suggested awareness, social influences and self-efficacy as crucial enablers and privacy and security risks and vulnerability concerns as crucial inhibitors towards m-payment adoption and usage.

As a novel contribution to the BOP, financial inclusion, sustainable development goals and m-payment literature, this study unfolds several unknown perceived benefits and perceived sacrifices that influence the BOP consumers’ m-payment adoption intention and usage. The study’s findings help the government and banks formulate and implement strategies to achieve financial inclusion among BOP consumers.

The current study aims to predict consumer complaint status (complainers or non-complainers) based on socio-demographic and psychographic factors and further to discern the differences in behavior disposition of consumer groups concerning determinants of consumer's tendency to exit (TE).

The research used survey-based data of 600 Indian consumers of three service sectors (hotel and hospitality, automobile service centers and organized retail stores). Chi-square automatic interaction detector (CHAID) decision tree analysis was used to profile consumers.

The results indicated that occupation; income; education; industry and attitude toward complaining were significant factors in profiling consumers as complainers or non-complainers. Further, determinants of TE (discouraging subjective norms, perceived likelihood of successful complaint, lower perceived switching cost, poor employee response, negative past experience and ease of complaint process) vary significantly across the groups of complainers and non-complainers.

The research questions in this study were tested with three service sectors consumers in India, so due care should be exercised in generalizing these findings to other sectors and countries. Study replication across other service sectors and countries is recommended to improve the generalizability of these findings with wider socio-demographic samples.

Firms striving for consumer retention and aim to extend their consumer life cycle can greatly benefit from the results of this study to understand the customer complaint behavior (CCB) specific to non-complaining (exit) behavior. The future researcher may benefit from replicating and extending the model in different industries for further contribution to the CCB literature.

To the best of the author's knowledge, there is no evidence of consumer segmentation based on their complaining behavior or socio-demographic and psychographic factors by employing CHAID decision tree analysis. In addition to illustrating the use of data mining techniques such as CHAID in the field of CCB, it also contributes to the extant literature by researching in a non-Western setting like India.

The real challenges in online crack detection testing based on guided waves are random noise as well as narrow-band coherent noise; and to achieve efficient structural health assessment methodology, magnificent extraction of noise and analysis of the signals are essential. The purpose of this paper is to provide optimal noise filtering technique for Lamb waves in the diagnosis of structural singularities.

Filtration of time-frequency information of guided elastic waves through the noisy signal is investigated in the present analysis using matched filtering technique which “sniffs” the signal buried in noise and most favorable mother wavelet based denoising methods. The optimal wavelet function is selected using Shannon’s entropy criterion and verified by the analysis of root mean square error of the filtered signal.

Wavelet matched filter method, a newly developed filtering technique in this work and which is a combination of the wavelet transform and matched filtering method, significantly improves the accuracy of the filtered signal and identifies relatively small damage, especially in enormously noisy data. A comparative study is also performed using the statistical tool to know acceptability and practicability of filtered signals for guided wave application.

The proposed filtering techniques can be utilized in online monitoring of civil and mechanical structures. The algorithm of the method is easy to implement and found to be successful in accurately detecting damage.

Although many techniques have been developed over the past several years to suppress random noise in Lamb wave signal but filtration of interferences of wave modes and boundary reflection is not in a much matured stage and thus needs further investigation. The present study contains detailed information about various noise filtering methods, newly developed filtration technique and their efficacy in handling the above mentioned issues.

The manufacturing industry is presently experiencing technological disruption on a global scale. Consequently, to tackle such disruption, firms are identifying a volatile, uncertain, complex and ambiguous (VUCA) scenario and seeking ways to counter it. Accordingly, this paper aims to investigate the employee performance through assessing organizational citizenship behaviour (OCB) among the shop floor employees of the fast-moving consumer goods (FMCG) industry where a high-performance work system (HPWS) has been implemented.

A descriptive research design was used in the study, and 395 shop floor employees working in leading multinational firms, with a minimum global turnover of US$1bn, were interviewed. These manufacturing firms were located in three industrial clusters in the northern part of India.

The results indicate that HPWS influences OCB. Most of the dimensions of HPWS and OCB were found to be positively associated. The findings also disprove the labour process theory in the context of the study.

The findings report a broad view of the relationship between HPWS and OCB in the Indian manufacturing context. The study offers the practical insights that HPWS is a universally accepted framework and that organizations should focus on the effective implementation of HPWS in a VUCA scenario, which is in line with past studies. The study also provides future directions for research.

This paper has established the relationship between HPWS and OCB in the manufacturing sector, especially for shop floor employees.

The provision of value, as a marketing issue, is receiving increasing attention from managers and scholars. This attention, in combination with strong calls for better quantification and stronger measures in marketing, has lead to increased interest in the assessment, quantified where possible, of the provision of value through buyer–seller relationships. This paper identifies dimensions of value provision through relationships in business markets with specific emphasis on the intangible aspects of value, which are important to long-term competitive advantage. The provision of value to the seller is the prime focus in this paper. The paper discusses the meaning of both tangible and intangible relationship value and the interplay between them and notes the importance of assessing the intangible part of the value, particularly the part which derives from the human aspects of the relationship. Despite their importance, the human aspects of relationships and their contribution to value is a sparse topic among researchers. The paper compares and evaluates potentially useful relationship and value conceptualizations. The paper discusses studies of relationship value and then outlines the results of a recent line of empirical research into the provision of value by a buyer to a seller that utilizes a framework synthesized from the intellectual capital literature. This recent research conceptualizes the potential for a seller's relationship with a buyer to provide intangible value to the seller in terms of, first, the resources available in the buyer and second, the capabilities of the buyer's boundary personnel to aid in facilitating the flow of those resources to the seller. The paper also includes the softer human aspects in the dimensions of value. These latter aspects are important to a full assessment of value. The paper concludes with a discussion of aspects of intangible relationship value that need further elucidation and will thus provide opportunities for future research.