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The purpose of this paper is to address both the evolutionary and control aspects associated with the management of artificial superintelligence. Through empirical analysis, the authors examine the diffusion pattern of those high technologies that can be considered as forerunners to the adoption of artificial superintelligence (ASI).

The evolutionary perspective is divided into three parts, based on major developments in this area, namely, robotics, automation and artificial intelligence (AI). The authors then provide several dynamic models of the possible future evolution of superintelligence. These include diffusion modeling, predator–prey models and hostility models. The problem of control in superintelligence is reviewed next, where the authors discuss Asimov’s Laws and IEEE initiative. The authors also provide an empirical analysis of the application of diffusion modeling to three technologies from the industries of manufacturing, communication and energy, which can be considered as potential precursors to the evolution of the field of ASI. The authors conclude with a case study illustrating emerging solutions in the form of long-term social experiments to address the problem of control in superintelligence.

The results from the empirical analysis of the manufacturing, communication and energy sectors suggest that the technology diffusion model fits well with the data of robotics, telecom and solar installations till date. The results suggest a gradual diffusion process, like any other high technology. Thus, there appears to be no threat of “existential catastrophe” (Bostrom, 2014). The case study indicates that any future threat can be pre-empted by some long-term social measures.

This paper contributes to the emerging stream of artificial superintelligence. As humanity comes closer to grappling with the important question of the management and control of this technology for the future, it is important that modeling efforts be made to understand the extant perspective of the development of the high-technology diffusion. Presently, there are relatively few such efforts available in the literature.

The purpose of this paper is to examine (1) how the recovery speed using promotional investment and (2) distributed production using additive manufacturing (AM) improve the resilience of the supply chain to manage any disruptions in the diffusion of green products.

The environmental performance, service level performance and economic performance are the measures of interest. These measures are studied through the integration of inventory and production planning (I&PP) of the reverse logistics system and consumer behavior using Bass (1969) model of diffusion of innovation under the paradigm of Industry 4.0 architecture. The Taguchi experimental design framework was used for the simulation analysis.

The adoption patterns based on the Bass model in conjunction with recovery speed and production on AM during the disruption period suggest that there exist tradeoff decisions between various combinations of information-sharing and I&PP policies.

The extensive sensitivity analyses provide real-time support for managerial decisions. Besides the potentials of Industry 4.0 capabilities, the present research suggests paying close attention to the recovery speed in conjunction with the inventory management system.

The integration of consumers' behavior (Bass model) to digital technologies is an additional contribution of the present research toward sustainability issues from the social perspective.

Previous research studies have discussed resilience to manage the ripple effect. However, none of them have addressed the changing scope of resilience to manage the ripple effect caused by the disruption in the diffusion of green products in a reverse logistics setup.

Security and safety have remained important concerns for mankind since ancient times. In the context of railways, however, the threat perceptions to safety and security have increased significantly lately. In view of this, the Indian Railways requires an effective and efficient security management system. The purpose of this paper is to propose an integrated approach to help develop the Indian railway security system (IRSS) by successively reducing the complexity of the system through a series of studies.

The relevant elements of the complex system of Indian Railways have been identified. The framework in which the elements exist and interact with each other has been clearly established using the interpretive structural modelling (ISM) technique. The output of ISM is further reduced in complexity by having different policy option profiles. A comparison of different option profiles has been done by a multi-criteria decision-making technique, the analytic hierarchy process (AHP), by choosing suitable criteria for comparison.

The following elements need to be pursued as the key objectives for making IRSS: protection of passengers, protection of property, modernisation, manpower enhancement, multi-skilling of staff, latest technology and enhanced legal powers.

The present research can be extended in many important ways. Interpretive structural models for different contextual relationships can be developed and used for formulating and implementing customised security policy. Policy elements and the ISM structure obtained in this research can be utilised for the system dynamic modelling of IRSS. A pilot study can be done to implement the recommendations made in this study.

The ISM model developed can be implemented as a policy tool in enhancing the railway’s security. Some of the policy elements proposed appear to be consistent with the strategic direction being undertaken in the railway security in the country.

Security is an important concern for mankind and social civilisations. The results have significant welfare implications in India and the rest of the world.

The present study is one of the first approaches in a series of studies in railway security in India. The results of this study can be extended to other security scenarios with similar needs.

Literature suggests that branding effectiveness measures are present in for-profit sectors but lacks such comprehensive measures for the non-profit sector. Moreover, most of the branding effectiveness measures are either based on brand image approach or on brand identity approach. The purpose of this paper is, therefore, to propose an integrated branding effectiveness measurement metrics for non-profit organizations (NPOs).

Judgmental and simple random sampling techniques are used for data collection. The final sample comprises 150 respondents including donors, volunteers, beneficiaries and media who were administered interview schedules. Based on the ratings given by the respondents regarding branding effectiveness parameters of the five NPOs of a major city in Northern India, branding effectiveness score of each NPO is computed. The branding measures adopted by NPOs rated high are selected in the proposed brand effectiveness metrics.

The proposed metrics encapsulates brand identity parameters such as management profile, vision, culture, as well as brand image parameters such as brand awareness, brand understanding, brand association of the stakeholders, etc. The metrics also link the two through brand performance parameters.

Multiple hierarchical structures of government infested with bureaucracy and lack of specialized staff with focused approach have reduced the effectiveness of their socio-development programs in emerging economies. This has led to an increase in number, diversity and impact of NPOs that compete for resource generation. Branding is a powerful tool for NPOs not only for resource generation but also for driving the social goals. The branding effectiveness metrics would help NPO managers reinforce the internal identity by increasing the cohesion and the capacity of the organization as well as create a strong brand image by garnering the support of multiple stakeholders through mutual trust thereby creating a greater social impact.

The uniqueness of the study stems from the fact that the proposed branding effectiveness measurement metrics in non-profit environment encapsulates brand image, brand identity and brand performance parameters.

The COVID-19 pandemic has brought unprecedented disruptions to global supply chains, compelling organizations to reevaluate their strategies for resilience and adaptability. In response, smart technologies (ST) have emerged as integral tools in post-pandemic supply chain management (SCM). This study aims to conduct an exploratory systematic literature review to comprehensively examine the evolving landscape of smart technology adoption in the context of SCM post-pandemic.

A systematic literature review has been conducted to examine the potential research contribution or directions in the field of ST and SCM. In total, 240 articles were shortlisted from the SCOPUS database in the chosen field of research. Bibliometric analysis was conducted by using VOSviewer to investigate the research trends in the area of SCM.

The review identifies key themes and trends, including supply chain resilience, digital transformation, enhanced visibility, predictive analytics and sustainability considerations. It explores the role of ST in fostering agility, transparency and risk mitigation within supply chains. Furthermore, eight clusters were identified to generate several thematic topics of ST in SCM. The results have evidenced a strong gap related to Industry 5.0 approaches for the supply chain field. A total of 240 publications, including journal articles, have been found in the literature. A total of 37 words, which were grouped in 8 clusters, have been identified in the data analysis.

By synthesizing the current state of literature, this study provides valuable insights for practitioners, policymakers and researchers seeking to navigate the complexities of post-pandemic SCM in an increasingly digitized and interconnected world. The findings highlight the transformative potential of ST and offer a roadmap for further exploration in this critical domain.

In this paper, the development path of the field of ST in SCM during the pandemic and the research constructs are presented and potential research directions are based on the bibliometric method.

This paper provides a managerial overview of social marketing in India to improve the understanding about its nature and utility in addressing the needs of India's social sector.

The study employs a qualitative research methodology by conducting an extensive review of relevant theories, concepts and past studies related to social marketing, focusing on the Indian context. Select case studies have also been studied and presented to elucidate how social marketing programs are conducted by various forms of organisations in India.

First, the meaning of social marketing, its distinction from commercial marketing and some pertinent challenges faced by social marketers are discussed. Thereafter, a brief overview of the role of competition, cost and barriers towards conducting an effective social marketing program is provided. Lastly, we propose a scheme of organisations sponsoring social marketing in India and discuss the future perspectives.

The study enables a deeper understanding of social marketing discipline for policy makers, social marketing professionals and organisations sponsoring social marketing initiatives in India.

The paper contributes to the literature on social marketing in the Indian context by conducting a broad overview with the aim of improving the understanding of social marketing which may help realise its full potential in the future.

The purpose of this paper is to study the impact of collaboration between supply chain entities in a dyadic setting where the manufacturer invests in greening and technology adoption effort leading to a price premium effect for the supply chain players.

The paper uses game theoretic approach to analyze the model of inter-firm interaction in a vertical channel setting consisting of a retailer and manufacturer. The paper studies strategic decisions of the channel members in a decentralized and centralized structure and extends this to decision making under contractual settings.

A two-part tariff completely coordinates the green supply chain, while a cost sharing and revenue sharing contract only achieve partial coordination. Nevertheless, a cost sharing, as well as a revenue sharing contract, increases the greening and technological adoption effort by the manufacturer while yielding the supply chain members a strictly larger profit. Furthermore, a revenue sharing contract in comparison to a cost sharing contract, leads to a larger greening and technological adoption effort by the manufacturer, lower wholesale and retail prices and a strictly larger profit for both the manufacturer and the retailer.

This paper contributes to the green supply chain pricing, technology and contract literature considering strategic interactions between a manufacturer and retailer in a supply chain under price premium effects of greening activities and technological advancements.

Physical security has remained an important reason for, and the consequence of, societal living. In recent times, the threat potential and the risks of loss and damage due to criminal activities have increased substantially. In Indian Railways, it is being increasingly felt that efficient security management is inevitable for the development and sustainability of desired state of affairs. The purpose of this paper is to address the broad goal of achieving optimal strategies for minimizing security threats to Indian Railway Security System (IRSS).

The authors use two forecasting techniques, namely, Delphi technique and Harva method, whose joint approach allows the authors to use both quantifiable (Delphi technique) and linguistic (Harva method) data. The choice of the two approaches provides a multi-method approach to the research problem.

Predicted trend toward the expected scenario in 2020 has more or less matched with the actual developments for improvement in security scenario of Indian Railways. The positive indications are that there is an improving trend, which is expected to lead to a much better state of affairs with certain inputs.

The joint approach of Delphi technique and Harva method is a multi-method example of original research work in the railway security, which can also be implemented in other security settings, such as aviation or marine security. A replication of the exercise closer to the target date will throw light on the exact state of affairs in the area of railway security in India.

An outcome in consonance with the present exercise has been the implementation of the policy developed on the basis of the forecasts. Policy efforts initiated in the recent past have been consistent with the features discussed in the study. From the above indicators, it can be inferred that some of the policy initiatives taken are in line with the trend status as predicted by the Delphi exercise.

Security has been considered as an important reason, as well as a consequence, of living in a society. It has been perceived as the condition of being protected against danger or loss, and also refers to the freedom from exposure to danger (protection), implying a feeling of assurance against danger. Research work in this area, thus, has strong social welfare implications. This is particularly so as the area of security gained importance, not only in India, but also across the world.

The present study is the first of its kind in the area of railway security using systems approach. The approach used is quite generic and can also be implemented in other security settings, such as aviation or marine security.

The purpose of this paper is to determine the inventory replenishment policies when demand rate is a function of the inventory space allocated to the products on retail shelves. Existing results on inventory policies with inventory-level-dependent demand (ILDD) assume deterministic functional forms of the demand rate. In this paper, the authors model the inventory decisions when demand is a function of shelf-space allocation and random uncertainty. The authors provide managerial insights of this paper's results.

The demand rate is assumed to be a function of shelf-space allocation based on two settings in the literature. First, the authors model the demand rate as a function of initial shelf-space allocation. In the next setting, the authors assume that the demand rate is a function of instantaneous inventory level on shelves. In both the settings, the authors also model random demand uncertainty in addition to the shelf-space dependency of demand rate. The objective is to maximize the expected profit and determine the inventory parameters.

In addition to the demand uncertainty, the authors consider linear, power and exponential functional forms of demand rate. Inventory policy that maximizes expected profit is determined when demand rate is a function of initial allocation and displayed inventory level. The results are implementable for practitioners for optimizing the shelf-space allocation and related inventory policy.

Most of the extant results on inventory policy with shelf-space-dependent demand do not model the demand uncertainty. The authors model a variety of functional forms of demand rate with ILDD in addition to the demand uncertainty. The results are a building block for more applications in inventory management for real-life applications.

This study proposes to understand the conditions favorable for readiness for organizational change. The analysis helps in proposing managerial interventions that would be useful for change management in an organization.

The study employs an empirical methodology to investigate the effect of individual and organizational factors on readiness for organizational change. The study has used descriptive research design. Bivariate linear regression is used to test the hypotheses, and multiple regression is used to identify the pertinent factor that affect individual's readiness for organizational change. Thereby, a causal relationship model is proposed, using few pertinent factors which are tested using the structured equation modeling (SEM) technique.

First, each of the factors independently has a significant effect on readiness for organizational change. Second, the prior experience of change, commitment towards organization and participation in decision-making are the pertinent factors that affect readiness for organizational change. Lastly, commitment towards organization partially mediates the relation between participation in decision-making and readiness for organizational change.

The analysis helps in proposing managerial interventions that would be useful for change management in an organization. It investigates how individual and organizational characteristics influence employees' readiness for organizational change, causing them to adopt the change process.

To the best of the authors’ knowledge, this is one of the first studies that investigates the pertinent individual factors and the organizational factors that affect readiness for organizational change in the context of an emerging economy, India.