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The main purpose of this study is to fill the research gap on how B2B global service firms integrate dynamic capabilities within their omnichannel management to influence positive word of mouth (WOM), customer engagement (CE) and customer equity.

Drawing on the dynamic capability and WOM theories, a model has been developed that defines the subjects of the empirical test. The paper reports on data collected from 312 service-oriented global firms in Australia, through a cross-sectional survey. Data were analyzed using structural equation modeling.

The findings suggest that content management (i.e. information consistency, source trustworthiness and endorsement) and concerns management (i.e. privacy, security and recovery) capabilities are the two significant antecedents of positive WOM within a B2B omnichannel setting in international marketing. The findings also confirm the key mediating role of CE between positive WOM and customer equity.

The findings extend dynamic capability theory in the context of international marketing by linking WOM, CE and customer equity. The findings add further theoretical rigor by establishing the nomological chain between positive WOM and customer equity, in which CE plays a key mediating role.

Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc.

In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021.

Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.

With the emergence of big data analytics and the importance of analytics-driven decisions, the travel industry is swiftly jumping on and adopting the bandwagon. However, research in this domain is limited. Accordingly, the present research seeks to understand how big data analytics capabilities (BDAC) add value to tourism supply chains (TSCs) and can dynamic capabilities (DC) improve the triple bottom line.

Data from 218 valid responses were collected from different Indian tourism industry units. Confirmatory factor analysis (CFA) was applied to confirm the constructs, followed by partial least squares structural equation modelling (PLS-SEM) to check the mediating effect of DC on TSCs performance.

The findings show that BDAC significantly influence the performance of TSCs and that DC plays a critical role in strengthening the impact of BDAC on TSCs' economic performance. These results corroborate that DC plays a key moderating role.

This study contributes significantly to the tourism sector in India, where tourism is a key contributor to the country's gross domestic product. Theoretically, this study contributes to the resource-based view (RBV) and practically encourages professionals in the tourism sector to promote the use of BDAC to enhance the performance of TSCs.

The originality of the study is that it has tried to comprehend the moderating role of dynamic capabilities which impact BDAC to improve TSC performance.

The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid the organisational managers and academics in enhancing the understanding of the human thought process and mitigate them suitably.

A multiple case study was conducted in organisations that were previously committed to Lean practices and had a multi-cultural work environment. This research was conducted on five companies based on 99 in-depth semi-structured interviews and seven process observations that sought to establish the system-wide cognitive biases present in a multi-cultural Lean environment.

The novel findings indicate that nine new biases influence Lean implementation and practices in a multi-cultural environment. This study also found strong connectivity between Lean practices and 45 previously identified biases that could affect positively or negatively the lean methodologies and their implementation. Biases were resilient enough that their influence on Lean in multi-cultural workplaces, even with transient populations, did not demonstrate cultural differentiation.

Like any qualitative research, constructivism and narrative analyses are subjected to understanding based on knowledge gained on the subject, and data may have been interpreted differently. Constructivist co-recreation of process scenarios based result limitations is therefore acknowledged. The interactive participation in exploring the knowledge sought after and interaction that could have a probable influence on the participant need to be acknowledged. However, the research design, multiple methods of data collection, generalisation based on data collection and analysis methods limit the effects of these and findings are reliable to a greater extent.

The results can provide an enhanced understanding of biases and insights into a new managerial approach to take remedial steps on biases’ influence on Lean practices that can result in improved productivity and well-being from a business process perspective. Understanding and mitigating the prominent biases can aid Lean manufacturing processes and support decision makers and line managers in improving lean methodologies’ effectiveness and productivity. The biases can be negated and used to implement decisions with ease. The influence of biases and the model could be used as a basis to counter implementation barriers.

To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes in a multi-cultural environment to identify the cognitive biases that influence Lean practices in organisations that were previously committed to Lean practices. The novel findings indicate that nine new biases and 45 previously identified biases influence Lean implementation and practices in a multi-cultural environment. The second novelty of this study shows the connection between cognitive biases, Lean implementation and practices in multi-cultural business processes.

This research paper aims to understand how givers characterise and manage their gift giving networks by drawing on attachment theory (AT). This responds to the need to illuminate the givers–receivers’ networks beyond traditional role-based taxonomies and explore their changing dynamics.

A multi-method, qualitative approach was used involving 158 gift experiences captured in online diaries and 27 follow-up interviews.

Results show that givers organise receivers into gifting networks that are grounded in a contextual understanding of their relationships. The identification of direct, surrogate and mediated bonds reflects three different dimensions that inform gift-giving networks of support, care or belongingness rooted in AT. The relative position of gift receivers in this network influences the nature of support, the type of social influences and relationship stability in the network.

This study illustrates the complexity of relationships based on the data collected over two specific periods of time; thus, there might be further types of receivers within a giver’s network that the data did not capture. This limitation was minimised by asking about other possible receivers in interviews.

The findings set a foundation for gift retailers to assist gift givers in finding gifts that match their perceived relations to the receivers by adapting communication messages and offering advice aligned with specific relationship contexts.

This study illuminates gift-giving networks by proposing a taxonomy of gifting networks underpinned by AT that can be applied to study different relationship contexts from the perspective of the giver. This conceptualisation captures different levels of emotional support, social influences and relationship stability, which have an impact on the receivers’ roles within the giver’s network. Importantly, results reveal that the gift receiver is not always the target of gift-giving. The target can be someone whom the giver wants to please or an acquaintance they share with the receiver with whom they wish to reinforce bonds.

This study aims to outline the current challenges in ultrasonic additive manufacturing (AM). AM has revolutionized manufacturing and offers possible solutions when conventional techniques reach technological boundaries. Ultrasonic additive manufacturing (UAM) uses mechanical vibrations to join similar or dissimilar metals in three-dimensional assemblies. This hybrid fabrication method got attention due to minimum scrap and near-net-shape products.

This paper reviews significant UAM areas in process parameters such as pressure force, amplitude, weld speed and temperature. These process parameters used in different studies by researchers are compared and presented in tabular form. UAM process improvements and understanding of microstructures have been reported. This review paper also enlightens current challenges in the UAM process, process improvement methods such as heat treatment methods, foil-to-foil overlap and sonotrode surface roughness to increase the bond quality of welded parts.

Results showed that UAM could solve various problems and produce net shape products. It is concluded that process parameters such as pressure, weld speed, amplitude and temperature greatly influence weld quality by UAM. Post-weld heat treatment methods have been recommended to optimize the mechanical strength of ultrasonically welded joints process parameters. It has been found that the tension force is vital for the deformation of the pre-machined structures and for the elongation of the foil during UAM bonding. It is recommended to critically investigate the mechanical properties of welded parts with standard test procedures.

This study compiles relevant research and findings in UAM. The recent progress in UAM is presented in terms of material type, process parameters and process improvement, along with key findings of the particular investigation. The original contribution of this paper is to identify the research gaps in the process parameters of ultrasonic consolidation.

The global financial crisis (GFC) of 2007–2008 had far-reaching consequences for the global economy, triggering widespread economic turmoil. We use the event-study method to investigate whether investors priced the effect of significant events before the Lehman Brothers' bankruptcy in European and Asia-Pacific banks. Abnormal returns on the event days range from −4.32% to 5.03% in Europe and −5.13% to 6.57% in Asia-Pacific countries. When Lehman Brothers went bankrupt on September 15, 2008, abnormal returns averaged the lowest at −4.32% in Europe and −5.13% in Asia-Pacific countries. The significant abnormal returns show that Lehman Brothers' collapse was a turning point, and investors paid attention to the precrisis events as warning signs of the oncoming crisis.

The purpose of this paper is to study the effect of corporate social responsibility (CSR) effectiveness on job seekers’ organizational attractiveness (JSA). Deriving inspiration from Carroll’s theory, the study specifically tries to measure the impact of CSR on JSA with the four dimensions pertaining to economics (PECO), pertaining to legal compliance (PLCO), pertaining to ethics (PETH) and pertaining to philanthropic (PPH). Furthermore, the paper also tries to examine the moderating role of company selection (COM SEL) done based on high or low CSR reputation and JSA.

Management and engineering students enrolled in premier institutions and universities of Western Odisha in India are surveyed for their perceptions of CSR and JSA. Purposive and convenience sampling are applied to collect data from 456 job seekers. Based on the analysis, the study proposes two main models (Models 1 and 2) wherein Model 1 tries to measure the effect of CSR on JSA and Model 2 checks the moderating effect of COM SEL on CSR and JSA. In addition, robustness of the study is tested using control variables (Models 3 and 4). Data is treated through SmartPLS 3.3 software. The structural equation modelling (partial least squares-SEM) method is applied to test the hypotheses and for further analysis.

The result reveals an interesting insight. There is a positive and significant effect of PECO, PLCO and PPH on JSA. Moreover, no such significant effect is observed between PETH and JSA. Further, the findings are contrary with respect to COM SEL, that partially moderates the effect of CSR on JSA. However, the results reveal that COM SEL has a substantial moderating effect on the PPH dimension of CSR and JSA.

The results highlight that CSR positively and significantly affects JSA in terms of PECO, PLCO and PPH, thereby emphasizing that organizations must be more focused on these perspectives of CSR. Further, though the results did not exhibit any significance with PETH, it is essential that organizations should strengthen the ethical aspects of CSR as well and align them with the CSR strategic actions. The study also confirms the moderating effect of COM SEL on PPH dimension of CSR and JSA, thereby supporting the philanthropic approach in this domain. Further, the organizations should foresee the philanthropic factor of CSR as a competitive advantage to attract potential job seekers.

This research attempts to contribute to CSR and HR literature in two ways. First, it is the first attempt to use PLS-SEM with an attempt to understand job seekers’ perception of CSR and JSA with Indian data consisting of students belonging to premier business management and engineering institutes. Second, the study is an attempt to empirically measure the moderating effect of COM SEL on JSA. To sum up, the study will provide insights to organizations to help craft CSR strategies for attracting more job seekers.

The emerging attention in big data has led businesses to improve big data analytics talent capability to enrich firm performance. The big data capability pays off for some companies but not for all, and it appears that very few have achieved a big impact through big data. Rooted in the latest literature on the knowledge-based view, IT capability, big data talent capability and business intelligence, this study aims to examine how big data talent capability impact on business intelligence infrastructure to achieve firm performance.

The primary survey data of 272 IT managers and big data analysts from Chinese firms was analyzed by using the structural equation modeling and partial least squares (Smart PLS 3.0). The analysis uncovers a positive and significant relationship in the proposed model.

The finding shows that the big data analytics talent capability positively impacts on business intelligence infrastructure that in turn directs to achieve firm financial and marketing performance.

This study theorized on the multitheoretic lenses, and findings suggest the managers and industry practitioners to develop business intelligence infrastructure capabilities from big data analytics talent capability.