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The purpose of this paper is to develop a framework for measuring retail productivity. It intends to identify all the constituents of retail productivity exhaustively, along with their measures and integrate them with a comprehensive model.

The paper summarizes the significant empirical works from the literature along with their study methods and identifies the gaps. The proposed methodology is a combination of various exploratory methods consisting of secondary data analysis, group interviews, depth interviews, observation and questionnaire survey.

A regression‐based conceptual model including each of the output and input variables of retail productivity. It also provides conception logic and measurement method for each of the variables. It identifies the control parameters too and proposes to handle them in the model. The empirical validation provides the significance of various input parameters.

The empirical validation is restricted to one retail format and one vertical (medium‐sized stores and apparel‐life style vertical). However, it provides significant input regarding the way to utilise retail productivity and the strategic directions to improve store level productivity.

The most significant usage of the model is the standardization of retail productivity concept as a performance measurement tool and its applicability in individual retail stores (micro level). Hence, it is possible to determine the reasons for performance of retail stores and develop appropriate as well as effective strategies. The identification and elaboration of the various parameters of retail productivity would help retailers to redefine and focus on key decision areas.

The paper presents the exhaustive framework for retail productivity with data from the Indian retail sector that is applicable at micro level. It provides direct measure of value component (services) in retail output determination.

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.

This study aims to empirically examine the relationship between Six Sigma and organisational performance of the Dubai Police Force (DPF). Moreover, this study further explores the role of innovation culture as a mediating variable between this relationship.

A questionnaire survey was conducted to collect research data. The population of the study was composed of head section officers of the DPF. A total of 388 questionnaires were distributed amongst respondents in which 252 of them were returned. Structural equation modelling was performed to test the hypothesised model.

Central findings confirmed the effect of Six Sigma and innovation culture on organisational performance. Additionally, innovation culture was found to partially mediate the effects of Six Sigma on organisational performance.

Findings from this study may enlighten managers, practitioners and academicians on the importance of using Six Sigma in the policing field. This study advocates taking into account preparing appropriate culture when implementing Six Sigma projects given its role in facilitating the implementation of these projects and achieving success. Six Sigma with innovation culture provides a key opportunity for the creation of uniqueness and has the potential to significantly influence organisational performance.

This study adds to the current knowledge on the role of Six Sigma on organisational performance of police agencies. This study is the first to provide empirical evidence on the mediating role of innovation culture on the relationship between Six Sigma and organisational performance in policing context.

The overarching objective of this research is to integrate the Lean Six Sigma (LSS) framework with computer simulation to improve the production efficiency of a light-emitting diode (LED) manufacturing factory.

Recently, the idea of taking advantage of the benefits of Six Sigma and simulation models together has led both industry and the academy towards further investigation and implementation of these methodologies. From this perspective, the present research will illustrate the effectiveness of using LSS methodology in a real factory environment by using the combination of three simulation methods which are system dynamics (SD), discrete-event simulation (DES) and agent-based (AB) modelling.

The hybrid simulation method applied in this research was found to accurately mimic and model the existing real factory environment. The define, measure, analyse, control and improve (DMAIC)-based improvements showed that the applied method is able to improve machine utilization rates while balancing the workload. Moreover, queue lengths for several stations were shortened, and the average processing time was decreased by around 50%. Also, a weekly production increase of 25% was achieved while lowering the cost per unit by around 8%.

While the case study used was for a LED manufacturing system, the proposed framework could be implemented for any other existing production system. The research also meticulously presents the steps carried out for the development of the multi-method simulation model to allow readers to replicate the model and tailor it for their own case studies and projects. The hybrid model enables managers to navigate the trade-off decisions they often face when choosing advanced production output ahead of continuous improvement practices. The adoption of methodologies outlined in this paper would attain improvements in terms of queue lengths, utilization, reduced costs and improved quality and efficiency of a real, small factory. The findings suggest improvements and create awareness among practitioners for the utilization of quality tools that will provide direct benefits to their companies. Although the multi-method simulation is effective, a limitation of the current study is the lack of micro details within each station. Furthermore, the results are all based on one specific case study which is not enough to suggest and generalized findings.

This research combines the use of the three main hybrid simulation paradigms (SD, DES and AB) in a unified framework DMAIC methodology. Choosing the right models in DMAIC is important, challenging and urgently necessary. Also, this paper shows empirical evidence on its effectiveness.