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Researchers have studied processes of improving road traffic-safety culture by explicitly evaluating the socio-psychological phenomenon of traffic-risk. The implicit traffic-system cues play an important role in explaining urban traffic-culture. This paper aims to ascertain an interpretive framework of the alternative processes of road traffic safety culture is antecedent to promote traffic-safety behaviour in Indian urban context. Subsequently, the authors discussed the reasons for those relationships exists.

Four experts of the urban traffic-safety domain participated in total interpretive structural modelling (TISM) study by completing an interpretive consensus-driven questionnaire. The drafted interpretive model was evaluated for road users proactive action orientation about the traffic-safety decision.

The evolved directed graph (digraph) of the culture of urban traffic-safety management was a serial three-mediator model. The model argued: In the presence of traffic-risk cues, people may become apprised to safety goals that initiate traffic-safety action. Consequently, expectancy-value evaluation motivates the continuation of traffic-safety intention that may lead to the implementation of adaptation plan (volitional control), thus habituating road users to traffic-safety management choice.

The modellers of traffic psychology may empirically estimate and test for the quality criteria to ascertain the applicability of the proposed mechanism of urban traffic-safety culture. The decision-makers should note the importance of arousal of emotions regarding traffic-risk, reduce the impact of maladaptive motivations and recursively improve control over safety actions for promoting safety interventions.

The authors attempted to induce an interpretive model of urban traffic-safety culture that might augment extant discussion regarding how and why people behave in an urban traffic system.

The main purpose of this paper is to investigate drivers and barriers of climate change mitigation strategies (CCMS), their linkages and impact in Indian Iron and Steel Industry (IISI) in light of ninth sustainable development goal (building resilient infrastructure, promote sustainable industrialization and foster innovation).

To identify relevant drivers and barriers, a thorough literature review and opinions of industry experts were obtained. Utilizing Total Interpretive Structural Modeling (TISM), the selected drivers and barriers were modeled separately along with Cross Impact Matrix-multiplication Applied to Classification (MICMAC).

Pragmatic and cost-effective technology, less supply chain complexity, robust policy and legal framework were found to have the highest driving power over all the other drivers. Findings suggest political pressure as the most critical barrier in this study. The results from TISM and MICMAC analysis have been used to elucidate a framework for the understanding of policymakers and achieve top management commitment.

This paper will help researchers, academicians, industry analysts and policymakers in developing a systems approach in prioritizing CCMS in energy-intensive (coal dependent) iron and steel plants. The model outcomes of this work will aid operational research to understand the working principles in other industries as well.

To the best of authors' knowledge, there is paucity of reported literature for the drivers and barriers of CCMS in iron and steel industry. This paper can be considered a unique, first attempt to use data from developing nations like India to develop a model and explain relationships of the existing drivers and barriers of CCMS.

The study aims to explore the role of digital economy and technology adoption for financial inclusion in the Indian context.

A conceptual framework was developed and hypotheses were tested through a survey conducted on 433 educated adults (males and females) residing in different districts of Rajasthan (India). Data was collected through a structured questionnaire and was subjected to confirmatory factor analysis. Structural equation modeling (second-order) was used to validate the measurement model and to test the mediating effect.

The measurement model is a confirmatory factor analysis and measures the reliability of the observed variables in relation to the latent constructs and indices shows the overall model fit. Structural model results indicate a complete mediation and a reflective impact (R² = 0.28) of the extended technology acceptance model on digital economy and financial inclusion relationship.

The study has taken into account only the perception of educated adults residing more specifically in one geographical area of a country. Thus, it limits the generalization of results in terms of implications to other regions and countries.

The proposed framework and implications are quite significant for policymakers and service providers to understand the nexus and strategic choices involved in this area. Moreover, understanding of user’s frame dependence would help in the development of digital assistive models that would perhaps mitigate the gap from participation (digital economy) to acceptance (financial inclusion).

Present study proposed a three-dimensional hypothetical model and conceptualized the digital economy (independent variable) as participation, behavioral intentions measured through the extended technology acceptance model (mediating variable) as adoption and financial inclusion (dependent variable) as acceptance to better understand the nexus. It represents the foremost step and a unique effort in this area. Moreover, the study was empirical and has wider applications both from the perspectives of end-users and service providers.

This work aims to review past and present articles about data-driven quality management (DDQM) in supply chains (SCs). The motive behind the review is to identify associated literature gaps and to provide a future research direction in the field of DDQM in SCs.

A systematic literature review was done in the field of DDQM in SCs. SCOPUS database was chosen to collect articles in the selected field and then an SLR methodology has been followed to review the selected articles. The bibliometric and network analysis has also been conducted to analyze the contributions of various authors, countries and institutions in the field of DDQM in SCs. Network analysis was done by using VOS viewer package to analyze collaboration among researchers.

The findings of the study reveal that the adoption of data-driven technologies and quality management tools can help in strategic decision making. The usage of data-driven technologies such as artificial intelligence and machine learning can significantly enhance the performance of SC operations and network.

The paper discusses the importance of data-driven techniques enabling quality in SC management systems. The linkage between the data-driven techniques and quality management for improving the SC performance was also elaborated in the presented study.

This paper aims to study the weak form of efficiency of Indian capital market during the period of global financial crisis in the form of random walk.

The study considered daily closing prices of S&P CNX Nifty, BSE, CNX100, S&P CNX 500 from April 1, 2005 to March 31, 2010. The data source is the equity market segment of NSE and BSE. Both parametric and nonparametric tests (“ex‐posts” in nature) are applied for the purpose of testing weak‐form efficiency. The parametric tests include Augmented Dickey‐Fuller (ADF) unit root tests and nonparametric tests include Phillips‐Perron (PP) unit root tests and Run test. ADF tests use a parametric autoregressive structure to capture serial correlation and PP tests use non‐parametric corrections based on estimates of the long‐run variance of ΔY_t.

The results suggested that the Indian stock market was efficient in its weak form during the period of recession. It means that investors should not be able to consistently earn abnormal gains by analysing the historical prices. Hence one should not be able to make a profit from using something that everybody else knows.

The study reports that all the stocks in these selected indices are fundamentally strong and their prices are not influenced largely by historical prices and other relevant factors which came from industry and any other information that is publically available. Thus it can be concluded that the Indian stock market was informationally efficient and no investor can usurp any privileged information to make abnormal profits.

Where past studies have examined the weak‐form of efficiency of various markets and the effect of globalisation and global financial crisis on the various sectors of developing and emerging economies, this paper attempts to study the weak form of efficiency of the Indian capital market in the period of recession in the form of random walk.

The purpose of this paper is to propose a low carbon culture (LCC) adoption model for gaining the right carbon capabilities by integrating the dimensions of flexibility or control and external or internal of competing values framework (CVF) with that of level of carbon emission (LCE).

This study reviewed literature related to low carbon supply chain, CVF and carbon capabilities to synthesize currently available frameworks for assessing culture and carbon-related insights. Based on these insights, this study proposes the carbon culture adoption model and presents some research propositions.

This study has extended categorization of culture suggested in CVF from four categories to eight distinct categories by adding “LCE” as a third dimension. The new categories of carbon culture are: “Red,” “Antagonist,” “Obligatory,” “Early Adopter,” “Follower,” “Transitive,” “Pragmatist” and “Green.” This categorization of organizations would help in selecting appropriate low carbon practices (LCPs).

This study presents purely conceptual framework with some research propositions which needs to be empirically tested.

Organizations can formulate right policies for low carbon capabilities based on the LCC of their supply chain.

With increasing awareness about environment across stakeholders, organizations around the world are under pressure to reduce their carbon footprints. The extent of reduction in carbon footprints depends on the right capabilities across the supply chain which in turn depends on selection of the right combination of LCPs based on the supply chain culture.

Black cumin (Nigella sativa L.) is well known for its strong, hot, peppery taste and has many nutritional, pharmaceutical and traditional therapeutic uses. The aim of this study was to investigate the antioxidant effect of different solvent extracts of black cumin seed to retard lipid and protein oxidation in raw ground pork meat during refrigerated storage (4 ± 1°C) for nine days.

Black cumin extracts (BCEs) were prepared using different solvents, namely, ethanol, water, ethanol:water (60:40) and methanol:hot water (60:40). Extracts were analysed for total phenolic content (TPC), 1,1 diphenyl-2-picrylhydrazil (DPPH) radical scavenging activity and reducing power. Based on the results, water extract (WE) and ethanol–water extract (EHWE) of black cumin were selected and incorporated at 1.5 per cent into freshly minced pork meat and compared with a synthetic antioxidant, butylated hydroxytoluene (BHT; 100 ppm), in retarding lipid and protein oxidation. Treated and control samples were aerobically packed in low-density polyethylene bags for analysis of various parameters (pH, colour and odour score, peroxide, lipid and protein oxidation) during nine-day refrigerated storage study.

Results showed that BCEs had a good amount of TPC (4.4-7.4 mg gallic acid equivalents/g) and also DPPH scavenging activities (33.96-44.23 per cent), with WE and EHWE extracts showing highest reducing power and promising antioxidant capacity. Hence, BCEs (WE and EHWE) incorporated at 1.5 per cent into freshly minced pork meat was tested, compared to BHT (100 ppm) and control samples, in retarding lipid and protein oxidation during storage. In BCE-treated samples, thiobarbituric acid reacting substances, free fatty acids, peroxide, formation of protein carbonyls and off-odour or rancid odour development were lower than control and values were comparable with BHT. Incorporation of BCE did not negatively affect the colour of ground pork.

BCEs (WE and EHWE) at 1.5 per cent inhibited protein and lipid oxidation and it could be exploited commercially as an effective alternative in retarding oxidative deterioration of meat products.

The different perspectives of diversity have until recently ignored emotional diversity primarily because emotions were discounted as “irrational.” To highlight the need for a broader integrative view of emotions in the workplace, the question addressed in the study was whether inclusive leadership helped emotionally reactive employees improve their performance and whether these employees displayed potential leadership qualities for future roles.

The study was qualitative. This cross-sectional study applied qualitative methods to gather the required information. Sixteen business heads across different sectors in India were purposively chosen for in-depth interviews with respondents. The interviews were semi-structured. The approach of theoretical sampling was adopted. From the initial set of questions, the next set of questions was evolved and the itineration was continued until saturation was achieved.

The results showed that mentoring and empowerment helped emotionally reactive employees improve their performance. On the question of their potential leadership role, the results were mixed.

The follower (protégé) perception, if also taken, can validate whether the person-centered style helped in the performance improvement of the followers. The responses of the leaders were based on their memory and no reports were checked from their office records to corroborate the same.

Researchers have argued that worker behavior and productivity are directly affected by employee affect and emotional states. The study contributes significantly to creating emotionally inclusive workplaces.

The study is focused on the role of diversity of emotions in the workplace impacting productivity. Emotions are vital and affect the workplace significantly. The study focused on what organizations could do to handle emotionally reactive employees at work. The study showed that inclusive leadership through mentoring and empowerment helped in assimilating difficult employees into the mainstream work.

The purpose of this study is to examine the implementation of human resource management (HRM) practices that facilitate innovation in the public sector in a developing country.

Qualitative method was engaged whereby a semi-structured interview was conducted to get the responses of two groups of employees which are top management and executive in two types of public organizations which are awarded and non-awarded. The collected data was later analyzed thematically.

The results show that there are differences and similarities among the public agencies in terms of their implementation of HRM practices that facilitate innovation. Apparently, the awarded public agencies do follow HRM practices that really facilitate innovation such as local training, provide more types of rewards to their employees and set a higher minimum level of innovation in their performance evaluation.

This research confines only 10 public agencies in Malaysia. Future studies might want to include a larger sample size to make the findings more extensive. It also would be interesting to know different approaches in HRM implemented in the private organizations as well as to examine their influences on performance and other organizational factors.

Good and fair HRM practices such as training, reward and performance appraisal practices that focus on innovation facilitate and produce more innovative employees and organization innovation. Thus, public managers should implement them to a higher extent.

To the best of the authors’ knowledge, this is the first study that aims to engage the qualitative method in understanding how HRM practices can facilitate innovation in a developing country.