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The purpose of this paper is to examine how organizational workers improve their perceived mobile user experience (UX) locus of control affected through organizational ambidexterity when using enterprise mobile systems (EMS). This study investigates the mediation role of business process customizability in the relationship between habitual use of EMS by individuals and organizational ambidexterity.

Over 150 possible respondent mobile phone users across 40 organizations in metropolitan National Capital Region (NCR) of Delhi with approximately were given the questionnaire. The data of a total of 121 NCR valid respondents aged between 22 and 49, after scrutinizing all collected questionnaires and removing those that had too many missing values or had the same answer to all questions, were used for analysis. The respondents were sampled from a research panel directory of a set of firms of the research firm hired for this survey.

The study finds complete mediation between the habitual use of EMS and organizational ambidexterity. Importantly, the empirical findings provide the research community with a deeper understanding of how EMS usage impacts organizational ambidexterity and individual’s UX locus of control.

It draws some newer areas of research with respect to interactions between enterprise mobile systems, business process customization due to enterprise mobile systems and organizational ambidexterity, which were hitherto unexplored.

Artificial intelligence (AI) is deemed to have a significant impact as a value driver for the firms and help them get an operational and competitive advantage. However, there exists a lack of understanding of how to appropriate value from this nascent technology. This paper aims to discuss the approaches toward knowledge and innovation strategies to fill this gap.

The discussion presents a review of the extant strategy and information systems literature to develop a strategy for organizational learning and value appropriation strategy for AI. A roadmap is drawn from ambidexterity and organizational learning theories.

This study builds the link between learning and ambidexterity to propose paths for exploration and exploitation of AI. The study presents an ambidextrous approach toward innovation concerning AI and highlights the importance of developing as well as reusing the resources.

This study integrates over three decades of strategy and information systems literature to answer questions about value creation from AI. The study extends the ambidexterity literature with contemporary.

This study could help practitioners in making sense of AI and making use of AI. The roadmap could be used as a guide for the strategy development process.

This study analyzes a time-tested theoretical framework and integrates it with futuristic technology in a way that could reduce the gap between intent and action. It aims to simplify the organizational learning and competency development for an uncertain, confusing and new technology.

The application of theories on group decision support is yet to be explored extensively in supplier selection literature, although the literature in both domains is extremely rich, in isolation. The purpose of this paper is to explore the application of group decision support theories for supplier selection.

The row geometric mean method (RGMM) of the analytic hierarchy process (AHP) has been used in this study for the prioritization of group preferences under consensus. A case study was conducted to test the theories of consensual group decision making and compare it with other approaches based on AHP.

The study establishes that the application of decision support theories for group decision making can improve the supplier selection process. Findings further imply that RGMM is more effective than eigen value method, for group decision making under consensus.

Methodologically, the study highlights the greater regularity in outcome of group decision making, vis-à-vis individual decision making, for the same decision-making context. Also, it highlights how RGMM is more effective since it preserves reciprocal properties and diversity in preferences better.

The study establishes that firms can improve supplier selection processes by leveraging on the collective expertise of a group rather than depending on individual decision-making expertise.

This study explores the application of different theories based on AHP for consensual group decision making. It compares different approaches based on AHP and establishes that RGMM is a superior approach for supplier selection.

Supplier selection studies have used a wide variety of supplier evaluation criteria, due to the diversity of the purchasing context. The purpose of this study is to identify the critical supplier selection criteria which are important across industries and across purchasing contexts, and subsequently estimate the importance of these criteria to the procurement practitioners.

First, a Delphi study has been conducted to identify the critical supplier selection criteria across manufacturing industries. Then, data were collected from 188 firms across 12 industries and analysed with fuzzy analytic hierarchy process for group decision making, to estimate the relative importance of these criteria.

Findings indicate that seven criteria are of critical importance to Indian manufacturing industries. Also evaluation criteria like product quality, delivery compliance and price have maximum criticality, while criterion like e-transaction capability is gaining in importance, with the increased adoption of e-procurement platforms.

The study has been conducted in India, while focusing on Indian manufacturing industries. Similar study conducted in developed economies may produce different results.

Findings will be useful for practitioners for benchmarking supplier selection processes, not only in India, but also in similar emerging economies. Also, the outcome will provide insights for suppliers for developing systemic improvements.

There has been no study in recent years which has attempted to estimate the importance of supplier selection criteria, while taking a multi-industry approach. This study identifies the critical evaluation criteria and estimates their relative importance to procurement experts.