An Evidence-Based CoCoSo Framework with Double Hierarchy Linguistic Data for Viable Selection of Hydrogen Storage Methods

Hydrogen is the new age alternative energy source to combat energy demand and climate change.Storage of hydrogen is vital for a nation’s growth.Works of literature provide different methods for storing the produced hydrogen,and the rational selection of a viable method is crucial for promoting sustainability and green practices.Typically,hydrogen storage is associated with diverse sustainable and circular economy(SCE)criteria.As a result,the authors consider the situation a multi-criteria decision-making(MCDM)problem.Studies infer that previous models for hydrogen storage method(HSM)selection(i)do not consider preferences in the natural language form;(ii)weights of experts are not methodically determined;(iii)hesitation of experts during criteria weight assessment is not effectively explored;and(iv)three-stage solution of a suitable selection of HSM is unexplored.Driven by these gaps,in this paper,authors put forward a new integrated framework,which considers double hierarchy linguistic information for rating,criteria importance through inter-criteria correlation(CRITIC)for expert weight calculation,evidence-based Bayesian method for criteria weight estimation,and combined compromise solution(CoCoSo)for ranking HSMs.The applicability of the developed framework is testified by using a case example of HSM selection in India.Sensitivity and comparative analysis reveal the merits and limitations of the developed framework.

Exploring the Reasons for Selfie-Taking and Selfie-Posting on Social Media with Its Effect on Psychological and Social Lives:A Study among Indian Youths

‘Selfie’taking was introduced to the common people by smartphones and has become a common practice across the globe in no time.With technological advancement and the popularity of smartphones,selfie-taking has grown rapidly within a short time.In light of the new trend set by the generation,this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults.A purposive sampling method was adopted to select 20 Indian citizens,between 18 and 24 years.The data were collected through semi-structured interviews and analysed using thematic analysis.Selfie-taking and posting on social media give positive feelings,and it acts as a mood modifier dependent mostly on the favourability and feedback about the post which in turn affects emotions and self-satisfaction.

Organizational dynamics of an information system: case study from the forestry sector

The Forest Department in the State of Uttar Pradesh, India developed Forest Management Information System (FMIS) for achieving organizational goals of improved financial and human resource management, improvement in the management of forests and wildlife, and for achieving responsive administration. This paper, based on field research, presents an assessment of the dynamics of FMIS in organizational context for a better understanding of such systems in forestry organizations. The paper also investigates the success of FMIS in assisting decision makers in achieving organizational goals. Based on the knowledge developed during the course of the study, key learning elements have been highlighted for the benefit of the stakeholders in information systems in forest sector.

Consumption Value of Digital Devices: An Investigation through Facebook Advertisement

Data collection represents the most effort-intensive stage of any marketing research exercise, especially in cases sampling frame is unavailable. Sub-optimal bypasses in form of student surveys or surveys employing convenience sampling have become common. In modern era, where laptops and smartphones enable easy accessibility of respondents online, this study utilizes Facebook advertisement as a source of data collection to measure the construct of user experience for interactive products. Modern digital devices, like smartphones, are a source of a variety of experiences for the user. Design teams at various smartphone manufacturers are struggling every day to create products which provide complete consumer experiences. This work not only proposes a framework for describing the same with usability, social value and pleasure in use, but also tests the scales for each by empirical validation. Data collection process through Facebook, as a sample frame, is something yet to be seen in marketing literature. This work goes the distance in not only demonstrating the efficacy of using Facebook advertisement as a viable data collection tool but also developing a framework to measure consumption value. Outcomes of the study, should promote further research using this sampling frame for future research, especially in the area of marketing.

How Product Importance Perception, Need for Cognition and Enduring Involvement Influence Investors＇ Knowledge of Investment Products？

The lack of proper knowledge about investment products can have a large negative influence on the financial well being of investors. Inspire of that, there is a dearth of studies conducted, specifically to investigate the factors influencing the knowledge of investors about investment products. This paper propose a model and investigates the direct and indirect （mediated through investor＇s enduring involvement with product） influence of investor＇s product importance perception （PIP） and need for cognition （NFC） on investor＇s knowledge of investment products. The hypothesized relationship is empirically validated in the context of mutual fund schemes （MFs）. Survey conducted on the sample of 268 MF investors suggests that there is an insignificant direct influence of investor＇s PIP and NFC on investor＇s knowledge of investment product （KIP）. However, when mediated through enduring involvement with product （EIP）, the influence was found to be significant. The results suggest that EIP perfectly mediates the influence of PIP and NFC on investor＇s KIP. The relevance of the results to the policy makers is also discussed.

Motivations of Individuals Participating in Social Media： A Cultural Perspective

Social media is an information technology that allows users to communicate and share information. With steadily rising number of users across the globe, individuals participate in various activities, like connecting with friends and community members, sharing information, posting political messages, disaster recovery activities, reading daily news, learning, and entertainment, each driven by different sets of motivations. Culture has an influence on the kind of motivation―pro-social and personal needs oriented―that drives social media usage by individuals. Using Hofstede’s （1984b） cultural dimensions, the paper suggests that each of the dimensions will have influences on the social media behaviors differently. Such a cultural perspective helps future social media users to plan the kind of activity and information sharing based on the kind of motivation driving the target audience and the platform providers to design and market accordingly.

The Role of Financial Performance as a Moderator on the Relationship Between Financial Leverage and Shareholders Return

The study examines the moderating effects of financial performance on the relationship between financial leverage （FL） and shareholders return （SR）. Panel data of pharmaceutical companies listed in the National Stock Exchange （NSE） were used for 13 years for the period from 2002-03 to 2014-15. Findings indicated that FL is significantly related with SR. However, financial performance has an insignificant relationship with SR and did not moderate the relationship between FL and SR.

Tabu Search Implementation on Traveling Salesman Problem and Its Variations: A Literature Survey

The Traveling Salesman Problem (TSP) and its allied problems like Vehicle Routing Problem (VRP) are one of the most widely studied problems in combinatorial optimization. It has long been known to be NP-hard and hence research on developing algorithms for the TSP has focused on approximate methods in addition to exact methods. Tabu search is one of the most widely applied metaheuristic for solving the TSP. In this paper, we review the tabu search literature on the TSP and its variations, point out trends in it, and bring out some interesting research gaps in this literature.

A Multi-Objective Obnoxious Facility Location Modelon a Plane

In this paper a Vertex Covering Obnoxious Facility Location model on a Plane has been designed with a combination of three interacting criteria as follows: 1) Minimize the overall importance of the various exist-ing facility points;2) Maximize the minimum distance from the facility to be located to the existing facility points;3) Maximize the number of existing facility points covered. Area restriction concept has been incor-porated so that the facility to be located should be within certain restricted area. The model developed here is a class of maximal covering problem, that is covering maximum number of points where the facility is within the upper bounds of the corresponding mth feasible region Two types of compromise solution methods have been designed to get a satisfactory solution of the multi-objective problem. A transformed non- linear programming algorithm has been designed for the proposed non-linear model. Rectilinear dis-tance norm has been considered as the distance measure as it is more appropriate to various realistic situa-tions. A numerical example has been presented to illustrate the solution algorithm.

Adoption of green finance and green innovation for achieving circularity:An exploratory review and future directions

There is growing attention from governments and regulators towards crucial matters such as climate change and global warming,resulting in a pressing need to investigate the factors that make it possible for businesses to engage in green finance(GF).The externality of environmental pollution prioritizes the need of green innovation(GI)in public management.GF distributes financial resources to the research and development(R&D)of clean energy and environmentally friendly goods and processes;it is complementary to the GI process for environmental protection.GF policies help to alleviate the impacts of financial constraints and GI impaired industries involving new products,processes,services and the global market.To better understand how GF and GI have functioned as a catalyst for circular economy practices,this paper seeks to present a historical and contemporary overview of these concepts.The research is thoroughly dissected by a systematic literature evaluation of articles from 2016 to 2023 that appear in peer-reviewed journals and are indexed in the SCOPUS database.To attain supply chain circularity,this article encompasses four major research themes concerning the adoption of GF and green technologies.The research also includes a network analysis of shortlisted articles to examine the overall citation trends.It is shown that several institutional theories are associated with the investigated area.As a final step,a framework is provided to illustrate how GF and GIs might be used to achieve supply chain circularity.The research findings provide a novel concept related to GF within the context of GI which are significant for environmentalists,policymakers,green investors,and researchers.Through its findings,the study provides a conceptual framework that promotes sustainable strategies to effectively balance financial considerations and environmental innovation.It helps to leverage the potential of green research and practice to create value for businesses and to benefit society at large.The analysis provides an unexplored and significant contribution to current literature in terms of delivering evidence of the past and present approaches to GF and GI in a circular economy.The results of this study will attract the attention of policymakers and stakeholders to develop and combine the two concepts in research and practice to attain environmental balance in the circular economy and to promote long term sustainability.

Implication of machine learning techniques to forecast the electricity price and carbon emission:Evidence from a hot region

The current study examines the significant determinants of electricity consumption and identifies an appropriate model to forecast the electricity price accurately.The main contribution is focused on eastern region of Saudi Arabia,a relatively hottest geographical area full of energy resources but with different electricity consumption patterns.The relative irrelevance of temperature as predicting factor of electricity consumption is quite surprising and contradicts the previous studies.In the eastern region,electricity price has negative association with electricity consumption.While comparing traditional and machine learning,it is found that machine learning techniques offer better predictability.Amongst the machine learning techniques,the support vector machine has the lowest errors in forecasting the electricity price.Additionally,the support vector machine approach is used to forecast the trend of carbon emissions caused by electricity consumption.The findings have policy implications and offer valuable suggestions to policymakers while addressing the determinants of electricity consumption and forecasting electricity prices.

Socialist Market Economy and the Challenge of ＇Social Management＇ in China

Paolo Urio is Professor Emeritus in the University of Geneva, Switzerland and teaches Public Administration and Management. In this book Urio has presented his findings and understanding of China on the basis of his very active involvement in the management of the second phase of the ＂Sino-Swiss Management Training Programme in the Public Sector of China.＂ He mentions in his book that the project lasted 6 years （1997-2003） and it was during these years that he got an opportunity to come into close contact with Chinese scholars, administrators, party cadres along with providing him an opportunity to travel the mainland extensively.

Extreme dependencies and spillovers between gold and stock markets:evidence from MENA countries

This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia.It contributes to the existing literature by(i)revisiting this question for the principal stock markets in the Middle East and North Africa(MENA)region and(ii)using the copula-quantile-on-quantile and conditional value at risk methods to detail the risks facing market participants provided with accurate information about various gold and stock market scenarios(i.e.,bear,normal,bull).The results provide strong evidence of quantile dependence between gold and stock returns.Positive correlations are found between MENA gold and stock markets when both are bullish.Conversely,when stock returns are bearish,gold markets show negative correlations with MENA stock markets.The risk spillover from gold to stock markets intensified during the global financial and European crises.Given the risk spillover between gold and stock markets,investors in MENA markets should be careful when considering gold as a safe haven because its effectiveness as a hedge is not the same in all MENA stock markets.Investors and portfolio managers should rebalance their portfolio compositions under various gold and stock market conditions.Overall,such precise insights about the heterogeneous linkages and spillovers between gold and MENA stock returns provide potential input for developing effective hedging strategies and optimal portfolio allocations.

A new Net Resource Factor Based Alternative Method to Calculate Revised Target in Interrupted One Day Cricket Matches

This paper proposes an alternative method to calculate the revised target in interrupted 50 overs One Day international (ODI) cricket matches. Existing Duckworth Lewis (D/L) method and its modified versions only take available batting resources of the batting team into account and ignore the individual player’s excellence to calculate the revised target. Here, it is worth mentioning that individual player’s excellence varies in reality, and therefore quality of the available resources may affect the revised target significantly. Further in D/L method, revised target calculation depends only on the available batting resources of the batting team and does not consider the available bowling resources of the fielding team. Proposed method overcomes these two shortcomings by taking individual player’s excellence and available bowling resources of the fielding team into account. Individual player’s excellence has been determined by Data Envelopment Analysis (DEA), a well-known non parametric mathematical programming technique. A new idea of “Net Resource Factor” has been introduced to capture both batting and bowling resources to calculate the revised target. To the best of our knowledge, this is the first attempt to incorporate the ability of individual players and bowling resources of the fielding team for calculating the revised target. A comparative analysis between the proposed method and D/L method has been carried out using the data of real ODI matches held in the past. To facilitate ground application of the proposed method, a flow chart and a “Net Resource Factor Table” have been designed.

Inverse Problem for a Time-Series Valued Computer Simulator via Scalarization

For an expensive to evaluate computer simulator, even the estimate of the overall surface can be a challenging problem. In this paper, we focus on the estimation of the inverse solution, i.e., to find the set(s) of input combinations of the simulator that generates a pre-determined simulator output. Ranjan et al. [1] proposed an expected improvement criterion under a sequential design framework for the inverse problem with a scalar valued simulator. In this paper, we focus on the inverse problem for a time-series valued simulator. We have used a few simulated and two real examples for performance comparison.

Stumbling Blocks in Cloud Computing Adoption Pathway： A Charter

Cloud computing is currently an embryonic domain in the area of information technology that possesses the power of transforming the way information technology （IT） services are delivered and maintained in the business world. Pay as per the usage kind of cost structure coupled with delivery of computing services through internet makes cloud computing an exciting and potential growth oriented information technology model compared with conventional computing services delivery models. Various additional features like scalability, flexibility and easy deployment process creates a window for the organizations even relatively smaller in size to get benefitted by the highly advanced ＆ modern technologies without incurring substantial cost. In spite of so many benefits of this new delivery model, concerns are beginning to grow about how safe an environment it is. Despite of all the hype surrounding the cloud, enterprise customers are still reluctant to deploy their business in the cloud. Security is one of the major issues which reduces the growth of cloud computing and complications with data privacy and data protection continue to plague the market. Other related concerns associated with the adoption of cloud computing include trust on service providers, loss of control and compliance issues. This paper is an attempt to explore security ＆ trust issues linked with cloud computing adoption in the Small and Medium Enterprises （SME） sector.

High Dimensionality Effects on the Efficient Frontier: A Tri-Nation Study

Markowitz Portfolio theory under-estimates the risk associated with the return of a portfolio in case of high dimensional data. El Karoui mathematically proved this in [1] and suggested improved estimators for unbiased estimation of this risk under specific model assumptions. Norm constrained portfolios have recently been studied to keep the effective dimension low. In this paper we consider three sets of high dimensional data, the stock market prices for three countries, namely US, UK and India. We compare the Markowitz efficient frontier to those obtained by unbiasedness corrections and imposing norm-constraints in these real data scenarios. We also study the out-of-sample performance of the different procedures. We find that the 2-norm constrained portfolio has best overall performance.

Research on value co-creation elements in full-scene intelligent service

Compared with common intelligent service,full-scene intelligent service has its uniqueness in high integration,synergy,and technological spillover.However,the traditional service or business model theories cannot precisely elaborate its sociotechnical contextual nature and value creation logic.To fill this knowledge gap,we provide initial insights into the value co-creation logic in full-scene intelligent service by exploring the value co-creation elements using a data-driven text mining approach.We analyzed 171 business reports on the full-scene intelligent service by the topic modeling using the Latent Dirichlet Allocation(LDA).The findings reveal three main clusters:value proposition,participants,and connection platform.This study presents a theoretical framework for a further exploratory case study and quantitative research on full-scene intelligent service.This study also helps small and medium-sized enterprises to explore and exploit value co-creation opportunities.

Rising Consumption of Animal Products in China and India:National and Global Implications

Over the past two decades, the consumption of animal products has increased rapidly in China and India, driven by rising income and large populations. Such strong demand for animal products could have substantial impacts on both their own and global food and feed demand and supply. This paper examines the nature of rising demand for animal products in China and India and discusses national and global implications.

Synchronized strategy to minimize vehicle dispatching time:a real example of steel industry

Time compression in supply chains is a crucial aspect involved in the integration of warehousing and transport operations in the manufacturing industries. Sup- ply chain flows could be interrupted due to many sources of delays that lead to additional time in dispatching process and reduction in customer service level. The problem considered in this paper consists of long waiting times of loading vehicles inside the plant. This work presents a simulation-based study to minimize vehicle dispatching time in a steel wire plant. Value stream map is developed to present a system perspective of processes involved in the overall supply chain. Process activity mapping is com- pleted to provide a step by step analysis of activities involved in the vehicle dispatch process. A simulation model is developed for the system and a new model is proposed to improve the delivery performance by mini- mizing vehicles＇ waiting time.