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Successful smart cities' implementation will require organisational leadership decision-making competences. The foundation of smart cities is digital technologies; many of these technologies are emerging technologies that require IT skills, which are scarce and will exacerbate the battle for talent between organisations. Filling the talent gap will necessitate global hiring, which has implications for organisational culture, cultural diversity and organisational leadership. Organisational cultural mix is an important contributor to leadership decision-making. However, decision-making is underpinned by trust. Blockchain is an emerging technology that has the potential to engender organisational trust in decision-making and, by extension, in the leadership with the ‘right’ organisational culture. Smart cities will be required to leverage emerging technologies to give business performance a competitive advantage and use emerging technologies’ applications to build a sustainable competitive advantage.

This study aims to examine the flow of unsteady mixed convective hybrid nanofluid over a rotating sphere with heat generation/absorption. The hybrid nanofluid contains different shapes of nanoparticles (copper [Cu] and aluminium oxide [Al₂O₃]) in the base fluid (water [H₂O]). The influence of different shapes (sphere, brick, cylinder, platelets and blades) of nanoparticle in water-based hybrid nanofluid is also investigated.

To analyse the nanomaterial, the flow model is established, and in doing so, the Prandtl’s boundary layer theory is incorporated into the present model. The bvp4c approach, i.e. finite difference method, is used to find the numerical solution of differential equations that is controlling the fluid flow. The effect of relevant flow parameters on nanofluid temperature and velocity profile is demonstrated in detailed explanations using graphs and bar charts, whereas numerical results for Nusselt number and the skin’s coefficient for various form parameters are presented in tabular form.

The rate of heat transfer is least for spherical-shaped nanoparticle because of its smoothness, symmetricity and isotropic behaviour. The rate of heat transfer is highest for blade-shaped nanoparticles as compared to other shapes (brick, cylindrical and platelet) of nanoparticles because the blade-shaped nanoparticles causes comparatively more turbulence flow in the nanofluid than other shapes of nanoparticle. Heat generation affects the temperature distribution and, hence, the particle deposition rate. The absorption of heat extracts heat and reduce the temperature across the rotating sphere. The heat generation/absorption parameter plays an important role in establishing and maintaining the temperature around the rotating sphere.

The numerical study is valid with the exception of the fluctuation in density that results in the buoyancy force and the functional axisymmetric nanofluid transport has constant thermophysical characteristics. In addition, this investigation is also constrained by the assumptions that there is no viscosity dissipation, no surface slippage and no chemically activated species. The hybrid nanofluid Al₂O₃–Cu/H₂O is an incompressible and diluted suspension. The single-phase hybrid nanofluid model is considered in which the relative velocity of water (H₂O) and hybrid nanoparticles (Al₂O₃–Cu) is the same and they are in a state of thermal equilibrium.

Study on convective flow across a revolving sphere has its applications found in electrolysis management, polymer deposition, medication transfer, cooling of spinning machinery segments, spin-stabilized missiles and other industrial and technical applications.

The originality of the study is to investigate the effect of shape factor on the flow of electrically conducting hybrid nanofluid past a rotating sphere with heat generation/absorption and magnetic field. The results are validated and provide extremely positive balance with the recognised articles. The results of the study provide many appealing applications that merit further study of the problem.

Changes are inevitable in risky and uncertain business environments of today’s volatile supply chains. The concept of flexibility originates from this need to mitigate the ill-effects of risks and uncertainty in supply chains. In this paper, an attempt is made to present an exhaustive review on supply chain flexibility (SCF) and its implementation to gain strategic advantages.

A citation analysis method is employed in this paper to discuss, analyse and apprehend the conceptual, empirical, analytical and simulation studies done in this field. In this paper, about 110 papers on flexibility from many reputed journals are examined to study and assimilate various aspects of flexibility.

SCF embraces a unified process-based view including the core processes such as procurement, sourcing, distribution and logistics and mitigates uncertainty or risks involved. The review helps to assimilate the key knowledge about relevant practices in SCF and helps to draw implementing strategies while offering managerial insight on the subject.

Citation and co-citation analysis is done to review the SCF literature. Efforts are made to investigate relevant papers from various journals regarding its ability to mitigate risk or aid in making strategic decision. The study, however, is limited to certain industries in the papers as per chosen approach here. The strategies described in here may further be verified by the researchers and practitioners pertaining to their study or industries focused.

It provides managerial insight for practitioners on how to use flexibility within the firm and across supply chain while considering various trade-offs.

This paper is unique as a review paper, as it encompasses various kinds of studies done on SCF from conceptual models to mathematical models. Further, it briefs with the current practices in industries/SC towards being flexible. It talks of various trade-offs in pursuit of flexibility and concludes while suggesting numerous research gaps and opening new dimensions for SCF research. It offers many managerial and academic implications.

The uncertainty of getting admission into universities/institutions is one of the global problems in an academic environment. The students are having good marks with highest credential, but they are not sure about getting their admission into universities/institutions. In this research study, the researcher builds a predictive model using Naïve Bayes classifiers – machine learning algorithm to extract and analyze hidden pattern in students’ academic records and their credentials. The main purpose of this research study is to reduce the uncertainty for getting admission into universities/institutions based on their previous credentials and some other essential parameters.

This research study presents a joint venture of Naïve Bayes Classification and Kernel Density Estimations (KDE) to predict the student’s admission into universities or any higher institutions. The researcher collected data from the Kaggle data sets based on grade point average (GPA), graduate record examinations (GRE) and RANK of universities which are essential to take admission in higher education.

The classification model is built on the training data set of students’ examination score such as GPA, GRE, RANK and some other essential features that offered the admission with a predictive accuracy rate 72% and has been experimentally verified. To improve the quality of accuracy, the researcher used the Shapiro–Walk Normality Test and Gaussian distribution on large data sets.

The limitation of this research study is that the developed predictive model is not applicable for getting admission into all courses. The researcher used the limited data attributes such as GRE, GPA and RANK which does not define the admission into all possible courses. It is stated that it is applicable only for student’s admission into universities/institutions, and the researcher used only three attributes of admission parameters, namely, GRE, GPA and RANK.

The researcher used the Naïve Bayes classifiers and KDE machine learning algorithms to develop a predictive model which is more reliable and efficient to classify the admission category (Admitted/Not Admitted) into universities/institutions. During the research study, the researcher found that accuracy performance of the predictive Model 1 and that of predictive Model 2 are very close to each other, with predictive Model 1 having truly predictive and falsely predictive rate of 70.46% and 29.53%, respectively.

Yes, it is having a significant contribution for society; students and parents can get prior information about the possibilities of admission in higher academic institutions and universities.

The classification model can reduce the admission uncertainty and enhance the university’s decision-making capabilities. The significance of this research study is to reduce human intervention for making decisions with respect to the student’s admission into universities or any higher academic institutions, and it demonstrates many universities and higher-level institutions could use this predictive model to improve their admission process without human intervention.

This study uses a moderated, regression model and data from four‐digit SIC manufacturing industries to examine the advanced manufacturing strategy based on organizational size. Its results confirm recent studies that high technology has a negative effect on to the size of an organization. This study also reveals that, contrary to some previous research, large and small firms respond differently to technological changes.

This study, utilizing an advanced manufacturing technology (AMT) intensity index, first, examines the variations in a company’s performance as a function of the simultaneous effect of organizational commitment and the dimensions of manufacturing technology intensity and, second, using the moderator hypothesis, examines a proposal that the greater the organizational commitment complemented AMT’s competences, the greater would be the performance impact of AMT. Results from the study indicate that elements described as complementary to AMT strengths (i.e. desire to keep membership and willingness to exert effort on behalf of the organization) interact negatively with AMT.

This article attempts to synthesize the contributions of Jagdish Sheth to the discipline. This is done by following the development of the field in various subdisciplines such that one can observe the impact Sheth's thinking has had on the field. This is the career of an “accidental marketer” who started as a social scientist, got interested in buyer behavior, and made his mark in that field. Noticing similarities between organizational buyer behavior and individual buyer behavior, he ventured into that field too. As a visionary, he started developing theories in international marketing in the seventies, which was a popular area that time. Similarly, he published a handbook on Customer Relationship Marketing and worked in the area before it became a major area of emphasis. As a multifaceted person, he has contributed to the practitioners through books and consulting projects. However, this article focuses mainly on his academic contributions including his research, teaching/mentoring, and his philanthropic activities.

The case offers a study of change management in the pharmaceutical industry in India.

The case is designed for undergraduate and postgraduate students to examine strategic decisionmaking in the context of mergers and acquisitions (M&As), firm capabilities and management practices. In particular, it has important pedagogical lessons for businesses eager to start operations in emerging countries. Students learn to recognize the unique nature of the pharmaceutical market and the factors affecting the demand and supply of drugs, including the economics of generics. The case can be discussed in one class session of approximately one-and-a-half to two hours duration.

In 2012, the pharmaceutical industry in India was undergoing dynamic changes. There was keen interest among MNC pharmaceutical giants to buy up Indian generic manufacturing companies since their revenues were drying up with the impending patent expirations of many blockbuster brand name drugs. Japan's Daiichi Sankyo's had taken over the largest Indian pharmaceutical company, Ranbaxy Laboratories, known for its heritage of process innovations and market leadership. However, after the acquisition, Ranbaxy slipped to third position in the domestic market and was facing multiple problems including net losses and falling share prices, cultural differences in management practices, recall of drugs from foreign markets and a US FDA ban on its manufacturing plants. Further, Ranbaxy had always been viewed as a national champion and a customer-friendly company but drug prices had increased after the merger causing problems of affordability. The new CEO of Ranbaxy was facing a dilemma: how to regain the company's position as the market leader. Students are asked to advise the CEO of Ranbaxy how to tackle the challenges arising from the integration of an Indian company with a Japanese company. More specifically, the case focuses on M&A as a strategy for growth and also touches on issues related to competition, regulation, innovation and corporate governance.

The case discusses the different motives behind the deal for Daiichi Sankyo and Ranbaxy and why it was a strategic move by both the alliance partners. The case also raises issues of corporate governance for the management of Ranbaxy and the need for a proactive corporate social responsibility (CSR) strategy. The case provides students with the opportunity to develop their analytical skills in a real-life setting and apply theoretical concepts to the consideration of the various issues raised by the acquisition deal.

Teaching notes are available; please consult your librarian for access.

Circular economy denotes future sustainability that allows optimum utilization of resources. In the present era of technology, plenty of innovations are happening across the world, and digital manufacturing is one of such innovations. However, there are several barriers which are impeding adoption of digital manufacturing in circular economy environment. The study explores the barriers of digital manufacturing initiatives in a circular economy and develops a methodological model to prioritize the identified challenges for automotive parts manufacturing industry.

Seven categories of challenges namely process, human resources, financial, collaboration, technological, security and leadership challenges were identified from literature and further validated with subsequent discussions with experts from the industry. The study is conducted in two phases, where in the first phase, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is used to define the priority and importance of seven categories of challenges. In second phase, the barriers are ranked using a Fuzzy Performance Important Index (FPII), taking into account contextual factors associated with the challenges and linked barriers, to determine the extent to which they impede the adoption of digital manufacturing in the sample automotive parts manufacturing company.

The “risk of data security and information privacy in connection with use of external data and protecting customer data” appeared as the most significant barrier to digital manufacturing in circular economy. Furthermore, technological challenges emerged as the most significant category of challenges followed by financial challenges in adoption of digital manufacturing in circular economy.

Identification of the identified barriers and understanding the interrelationships will lead to easier adoption of digital manufacturing in circular economy.

Despite all the potential benefits of implementing Industry 4.0 technologies in manufacturing industries, the adoption thereof is still in nascent phase with significant challenges yet to be overcome to accelerate the pace of adoption. Hence, this study explores the barriers preventing companies from adopting and benefiting from digital manufacturing initiatives and further develops a methodological model.