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The purpose of this study is to investigate the impact of business group (BG) affiliation on affiliated firms' entrepreneurial orientation (EO). The authors further investigate the possible contingent factors affecting this relationship – the age of BGs and the affiliated firm’s external linkages (ratio of external to in-house interlocks) on the relationship in an emerging market context.

The study employs a dynamic panel data framework using the system-generalized method of moments (Sys-GMM) on a sample of 670 NSE-listed Indian firms during the 2006–2019 period. EO is measured through content analysis of the letters to shareholders (LTS) issued by the companies between the period 2006 and 2019.

BG affiliates have more EO than standalone firms, as affiliates can access group-wide resources and capabilities apart from firm-specific resources. Affiliates of older BG have less EO since they are more entrenched in the institutional settings of their BG. Affiliates with more external linkages of board members will have a higher level of EO, as such linkages would subside inertial tendencies by exposing them to novel sets of information, resources and strategic practices. Further, the negative effect of BG age on EO is countered by external linkages. Overall, the study shows that the effect of group affiliation is not uniform and is contingent on the factors we have theorized and tested.

The paper proposes the resource-based view and the institutional void theory as likely candidates for explaining the contribution of BGs towards the EO of its affiliates, especially in the context of emerging markets. The contingent role of BG age highlighted in the paper forewarns managers about the importance of establishing internal mechanisms to preserve the EO in affiliates. Our findings about the positive role played by external linkages of the board members provide one such mechanism that can be leveraged to enhance affiliated firm’s EO.

The purpose of this paper is to propose and develop PA2200-based composite powder containing 0-15 Wt.% magnesium oxide before directly using it in selective laser sintering (SLS) machine to produce end-use products for low-volume production in the engineering applications with keen focus to meet the functional requirements which rely on material properties.

The methodology reported emphasises PA2200-based composite powder containing 0-15 Wt.% magnesium oxide development for SLS process which starts with preparation and characterisation of composite material, thermal and rheological study of composite material to decide optimum process parameters for SLS process machine to get optimal part properties. Further, to verify composite material properties, a conventional casting methodology is used. The composition of composite materials those possessing good properties are further selected for processing in SLS process under optimal processing parameters.

The process parameters of SLS machine are material-dependent. The effect of temperature in X-ray diffraction profile is negligible in the case of magnesium oxide reinforced PA2200 composite material. The cyclic heating of material increases melting point temperature, this grounds to modify part bed temperature of material every time before processing on SLS machine to uphold build part properties, as well as material. With the rise in temperature, the Melt flow index and rheological property of materials change. The magnesium oxide reinforced PA2200 composite material has high thermal stability than pure PA2200 material. By the addition of small quantity of magnesium oxide, most of the mechanical property and flammability property improves while elongation at break (percentage) decreases significantly.

The proposed PA2200-based composite powder containing 0-15 Wt.% magnesium oxide material development system and casting metrology to verify developed material properties will be very useful to develop new composite material for SLS process with use of less material. The developed methodology has proven, especially in the case where non-experts or student need to develop composite material for SLS process according to the property requirement of applications.

Unlike earlier composite material development methodology, the projected methodology of polymer-based composite material and confirmation of material properties instead of commencing SLS process provides straight forward means for SLS process composite materials development with less use of the material and period of time.

This study aims to compare the fundamental indexation (FI) portfolio vis-à-vis the cap-weighted index (CWI). It also explored the return-generating attributes of the FI portfolios.

This study extracted relevant data from the Centre for Monitoring Indian Economy’s Prowess database from March 1996 to March 2017 from a sample of National Stock Exchange (NSE) 500 companies. The FI portfolios were constructed with First_50 and Next_50 stocks using the latest and five years of trailing average aggregations. Further, the regression technique was used to identify the return-generating attributes of FI portfolios.

It was found that the FI portfolios based on First_50 and Next_50 stocks outperformed the CWI (i.e. NSE_First_50 and NSE_Next_50) in the Indian capital market, and between the two, the FI portfolios based on Next_50 stocks were superior to the FI portfolios based on First_50 stocks. The cross-sectional superiority of FI portfolios is obvious if they are sorted according to four fundamentals, namely, total income, sales, operating cash flows and profit before depreciation interest tax and amortisation. The return-generating process of FI portfolios is well-explained by market premium followed by value premium and investment premium.

This study may enable portfolio managers and investors to measure FI portfolios’ superiority in the Indian capital market and identify the return-generating attributes of FI portfolios so that the loadings can be switched amongst different priced factors for higher yield. Further, this study extends the FI literature, providing evidence from one of the world’s fastest-growing economies.

To the best of the knowledge, this is amongst the first few studies to explore the performance of FI portfolios vis-à-vis CWIs in India, and to use Fama and French (2015) asset pricing models to understand the return-generating attributes of FI portfolios. It is also novel in the sense that it considers the FI portfolios for a longer duration, predating 1997 and coinciding with the inception of CWIs, namely, NSE_First_50 (inception: 1995) and NSE_Next_50 (inception: 1996), reducing the apprehensions of data-snooping biases.

The purpose of this paper is to propose and evaluate the selection of materials for the selective laser sintering (SLS) process, which is used for low-volume production in the engineering (e.g. light weight machines, architectural modelling, high performance application, manufacturing of fuel cell, etc.), medical and many others (e.g. art and hobbies, etc.) with a keen focus on meeting customer requirements.

The work starts with understanding the optimal process parameters, an appropriate consolidation mechanism to control microstructure, and selection of appropriate materials satisfying the property requirement for specific application area that leads to optimization of materials.

Fabricating the parts using optimal process parameters, appropriate consolidation mechanism and selecting the appropriate material considering the property requirement of applications can improve part characteristics, increase acceptability, sustainability, life cycle and reliability of the SLS-fabricated parts.

The newly proposed material selection system based on properties requirement of applications has been proven, especially in cases where non-experts or student need to select SLS process materials according to the property requirement of applications. The selection of materials based on property requirement of application may be used by practitioners from not only the engineering field, medical field and many others like art and hobbies but also academics who wish to select materials of SLS process for different applications.

The purpose of this study is to investigate the various challenges of humanitarian supply chains (HSC) and how these challenges can be addressed using artificial intelligence (AI).

This study employs exploratory analysis to identify various issues in HSC and the use cases of AI to address these issues through published literature. Subsequently, we collected tweets from Twitter and posts from LinkedIn using relevant keywords over four months. The collected data were cleaned, analyzed and interpreted to gain insights into users' perspectives on the various issues and use cases of AI in HSC.

The analysis reveals that various issues of HSC such as logistical challenges, security concerns, health and safety, access constraints, information gaps, coordination and collaboration, cultural sensitivity, funding constraints, climate and environmental factors and ethical dilemmas are predominantly discussed in published literature. Meanwhile, user-generated content reveals different levels of prioritization of these issues and AI attributes and offers AI-based solutions.

This study is subject to certain limitations, including a restricted data collection period of only four months and the use of just two social media platforms. These limitations could be addressed by conducting a more comprehensive and extended data collection across additional platforms to produce more conclusive findings. Another limitation is the lack of contextual information, which may have provided more specific insights.

To the best of the authors’ knowledge, this is possibly the first paper to explore both published literature and the collective intelligence of social media users to examine AI attributes, the various challenges of HSC and how AI can address these challenges.

This study aims to comprehend the application of analytics in the supply chain during the ongoing COVID-19 crisis and identify the emerging themes.

The author downloaded a list of research articles on the application of analytics to the supply chain from SCOPUS, conducted a systematic literature review for exploratory analysis and proposed a framework. Notably, the author used the topic modeling technique to identify research themes published during the ongoing COVID-19 crisis and thereby underscore some future research directions.

The author found that artificial intelligence, machine learning, internet of thing and blockchain are trending topics. Additionally, the author identified five themes by topic modeling, including the theme “Social Media information in Supply chain.”

The results were derived from a data set extracted from SCOPUS. Thus, the author excluded all studies not listed in SCOPUS from the analysis. Future research with articles indexed in other databases should be investigated to get a more holistic perspective of specific themes.

This study provides a deeper understanding and proposes a framework for applications of analytics in the supply chain that researchers could use for future research and industry practitioners to implement in their organizations to make a more sustainable and resilient supply chain.

This study provides exploratory information from published articles on the use of analytics in the supply chain during the COVID-19 crisis and generates themes that help understand the emerging and underpinned area of research.

The purpose of this paper is to holistically study barriers in the path of implementation of retirement planning, as the need is increasing with decrease in mortality. The proper retirement planning can be one of the most important tools to control financial expenses on healthcare and welfare on old age population in government budgets.

The paper is a blend of theoretical framework and practical application and uses interpretive structural modeling (ISM) analysis to draw linkage and impact of identified barriers in the path of achievement of goals of retirement planning. The study has used three different research phases: identification of barriers from the literature, interviews with experts of industry at second stage and designing an ISM impact matrix cross-reference multiplication model. The identification phase led to the selection of 15 factors from past literature and by suggestion from industrial experts.

This study seeks to identify which barrier is acting as the most dominant one for the mass adoption of retirement planning and this result is helpful for policymakers to remove the dominant barrier. The result of this analysis can make retirement planning easy by elimination of highlighted barriers on the basis of their importance in the path of achievement of retirement goals. In the ISM level diagram, barriers such as marital status, number of financial dependents at the bottom, gender, income level, educational level, financial literacy, financial dependency, policy regulation, terms and conditions, goal clarity and psychological and cultural factors are on the top. Barrier of macroeconomic and bureaucratic impediments are also very important factors for achievement of retirement goal of an individual, but they cannot be controlled directly by the associated members of industry.

The concern for providing sufficient retirement resources is growing with the increase in life expectancy for human beings. Such requirement has attracted views from not only academicians but also policymakers. This paper is one of the preliminary attempts to identify barriers in implementation of retirement planning and rank them according to their importance.

In this chapter, an attempt has been made to develop a security-based hardware system using an 8-bit single-chip microcontroller in conjunction with some sensor technology and lighting and alarming actuators. The proposed system aims to ensure the security and privacy of a dedicated area in terms of unauthorized human intrusion, hazardous gas leakage, extreme prolonged temperature changes, atypical smoke or vapor content in space and abrupt drop in illumination. The proposed system is capable of detecting any type of physical intervention and hazardous anomalies in the environment of the reserved space. In order to define the operation of the system, programs written in C++ with the special rule of code structuring have been deployed on the microcontroller using the Arduino Integrated Development Environment. The system is like a small container, enclosing all the respective sensor modules, microcontroller board and open connections for actuators. The proposed system is easy to use hardware and does not demand any human intervention for its functioning and can be installed with almost no changes in the infrastructure.

India is a rapidly urbanizing developing country with a population of 1.4 Billion. Indian governments have invested USD 50 Billion) in metro rail projects in 18 cities. Metro constructions are multi-stakeholder mega-projects and are prone to a variety of risks. The purpose of this paper is to analyze the risks involved in metro rail construction projects in a densely populated developing country for two types of systems and from two perspectives. Current literature lacks an understanding of similarities and differences in the risks involved in underground and elevated metro projects from clients' and contractors' perspectives, which the paper highlights.

A total of twenty-five risks were identified, categorized and assessed through experts' opinions about the impact and probability of occurrence of the risks through a questionnaire-based survey. The survey respondents included experts in metro rail construction from client and contractor sides. Paper uses a Fuzzy Inference System to calibrate risk magnitude from occurrence probability and impact.

A notable difference was observed in the views of clients and contractors, except for certain common risks. Both stakeholders had different risk perceptions for the underground and elevated metro rail systems.

This study contributes to the risk assessment for different types of metro systems. This research can help policymakers as well as consultants in prioritizing their risk management strategies in developing countries like India.

Highlighting the critical aspects of risks in metro projects in a developing country, this paper also provides system-based and stakeholder-based comparative aspects of risk analysis.

The changes in tensile behavior of polycrystalline nanocopper lattice with changes in temperature, average grain size (AGS) and strain rate, have been explored. The existence of a critical AGS has also been observed which shows that the Hall–Petch relationship behaves inversely.

Nanoscale deformation of polycrystalline nanocopper has been done in this study with the help of an embedded atom method (EAM) potential. Voronoi construction method has been employed for creating four polycrystals of nanocopper with different sizes. Statistical analysis has been used to examine the observations with emphasis on the polycrystal size effect on melting point temperature.

The study has found that the key stress values (i.e. elastic modulus, yield stress and ultimate tensile stress) are significantly influenced by the considered parameters. The increase in strain rate is observed to have an increasing impact on mechanical properties, whereas the increase in temperature degrades the mechanical properties. In-depth analysis of the deformation mechanism has been studied to deliver real-time visualization of grain boundary motion.

This study provides the relationship between required grain size variations for consecutive possible variations in mechanical properties and may help to reduce the trial processes in the synthesis of polycrystalline copper based on different temperatures and strain rates.