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The purpose of the study is twofold. The first objective is to identify adoption barriers (AdoBs) in engaging young consumers in the Omni-channel retailing (OCR). The second objective is to develop interrelationship among identified AdoBs.

The study used interpretative structural modeling–fuzzy ( Matriced’ Impacts Croisés Multiplication Appliquée a UN Classement) methods on 18 AdoBs identified from the existing literature and validated from 10 experts and 137 young consumers through pairwise comparison using the arithmetic hierarchical process method. The resulting ten barriers were further investigated for identifying the strength of relationships among them.

The study has identified price inconsistency as the dominant AdoB that restricts young consumers in engaging with OCR. The other critical AdoBs include lack of coordination among the channels, and information sharing and inconsistent price discount are the main barriers that affect all the other barriers among the 10 AdoBs identified in this study. The data also revealed that the young consumers exhibit the research-online purchase-offline effect in the purchase process.

The research study has undertaken ten barriers only. The interrelationship among the barriers may be tested further with advanced techniques. The data have been collected from young consumers of emerging markets only which may be further extended for other markets.

This study helps practitioners and decision-makers understand about AdoBs faced by the young consumers influencing the purchase-intention process. Retailers or marketers are encouraged to focus on price consistency, advanced shared information system, proper coordination and developing trust of consumers in sharing their data to enhance the acceptability of Omni channels. Moreover, the identification of barriers and their strength offer marketers or retailers an opportunity to engage them in an effective manner and thus create value using communication channels.

Social benefits of understanding barriers are helpful for transforming the existing retail channel into a fully integrated Omni-channel ecosystem. For this, AdoBs identified and their inter-relationships explored in this study could be used for engaging young consumers in OCR.

To date, the research on Omni-channel barriers in the present context is scant. The research provides insides on identified dimensions on young consumer engagement in OCR.

This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.

The experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.

The results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speed V_c = 80 m/min, feed rate f = 0.05 mm/rev. and depth of cut a_p = 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.

The research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

Currently, the bulk of research on marketing innovation focuses on various firm-level dimensions using relationships from the technological (product and process) innovation literature. Research on industry-level differences in marketing innovation is lacking. Testing relationships form the technological paradigm in the context of the marketing innovation paradigm is also lacking. This paper aims to present empirical evidence on both aspects using a large-scale data set.

This study uses two large-scale datasets, each consisting of approximately 4,000 Canadian enterprises in 18 industries. The data was collected by Statistics Canada in 2009 and 2012 through its nationwide Survey of Innovation and Business Strategies program. Two widely used theoretical frameworks, resource-based view of the firm and the competitive perspective, are used to generate constructs and hypotheses in relation to marketing innovation. The data was analyzed using multi-level logistic regression.

The findings show that industry-level competition is a much more important driver of marketing innovation than firm-level competition. The authors also show that marketing constructs that are significant in the context of technological innovation are also significant for marketing innovation.

This study extends the firm-level literature by providing evidence of how industry-level dynamics enhances marketing innovation. The study also provides empirical evidence from Canadian enterprises that complement those from other countries.

A deeper understanding of the drivers of marketing innovation can enable managers to enact innovation strategies that can enhance organizational performance, differentiate themselves and enhance customer engagement and brand image.

As one of the few studies to examine industry-level differences in marketing innovation, the authors show that disaggregating competition into industry-level and firm-level provides a clearer picture of how competition advances marketing innovation. Additionally, this study is the first of its kind to provide empirical evidence on Canadian enterprises, thereby complementing evidence on marketing innovation from other countries. Thus, this study makes a theoretical and empirical contribution to the emerging marketing innovation literature.

This study proposes a digital humanitarianism dynamic capability (DHDC) paradigm that explores the direct effects of DHDC on disaster risk reduction (DRR) and the mediating effects of process-oriented dynamic capabilities (PODC) on the relationship between DHDC and DRR.

To validate the proposed model, the authors used an offline survey to gather data from 260 district magistrates in India managing the COVID-19 pandemic.

The results affirm the importance of the DHDC system for DRR. The findings depict that the impact of PODC on DRR in the DHDC system is negligible. This study can help policymakers in planning during emergencies.

Technological innovation has reshaped the way humanitarian organizations (HOs) respond to humanitarian crises. These organizations are able to provide immediate aid to affected communities through digital humanitarianism (DH), which involves significant innovations to match the specific needs of people in real-time through online platforms. Despite the growing need for DH, there is still limited know-how regarding how to leverage such technological concepts into disaster management. Moreover, the impact of DH on DRR is rarely examined.

The present study examines the impact of the dynamic capabilities of HOs on DRR by applying the resource-based view (RBV) and dynamic capability theory (DCT).

Outlines previous research on four explanations for and various factors influencing dividend policy; and reports a survey of senior managers in US listed companies to determine their views. Finds strong support for the signalling explanation and some support for the bird‐in‐hand, tax‐preference and agency costs explanations, especially from regulated companies. Ranks the perceived importance of 20 factors influencing policy and discusses the top five (future earnings, past dividends, share price, concern over false signals and cash flow); and the differences between regulated and unregulated companies. Compares the rankings with Farrelly, Baker and Edelman (1986), recognizes the limitations of the study and considers consistency with other research.

The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.

The purpose of this paper was to first identify and then model the impact of critical success factors (CSFs) of public–private partnership (PPP) power projects.

Review of empirical literature came out with 20 CSFs which were ranked by experts and industry practitioners through a two-round Delphi questionnaire survey.

These CSFs were grouped into CSF groups (CSFGs) using component analysis, and they served as the input variables for fuzzy analysis. The six components were collaboration and transparency, guarantee and permits, socio-political support, expected profitability, technical feasibility and risk allocation (RA). Overall success index of PPP power projects in Ghana was 5.966 and showed there is high impact of CSFGs on project success. Fuzzy analysis also confirmed RA as the most significant CSFG.

The model developed can serve as a multi-dimension CSF framework that can be used as a success attainment tool for PPP power projects. For policy developers and stakeholders, the model serves as a pointer to issues which the government/public sector must focus on to attract huge investments from the private sector in the power sector.