Search results

This study aims to identify the major factors influencing the consumers to prefer milk products and also to analyze the awareness level of the Indian consumers.

In this study, the data is obtained through a structured questionnaire from Indian consumers considering convenience sampling under the nonprobability sampling technique. The consumer preference is explained using a multiple-regression model followed by analysis of variance (ANOVA), which shed insight on the significant differences between the variables that influence consumer preference for dairy products.

Investigation is done to analyze the factors influencing the consumers' buying behavior toward milk and its products. The results showed that quality, health consciousness, price and availability are the most influencing factors to buy milk products. Quantity of milk showed a significant relationship between age, monthly income and family size.

This study helps marketing managers to frame the marketing strategies based on consumer preference, quality, health consciousness, price and availability. The research outcome will not only be advantageous for the entrepreneurial perspective but also takes care of consumer likeliness. Though the research reveals the opinion of Indian consumers, it limits the likeliness of the western world. Because of the scarcity of resources, several dairy products are unexplored, which could pave the future scope of research.

The novelty of this study is to identify the quality, health consciousness, price and availability are the most influencing factors to buy milk products considering ANOVA and the multiple regression model.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

Personal Protective Equipment plays an inevitable part in the current scenario of pandemics in the world. A novel coronavirus, Severe Acute Respiratory Syndrome-Corona Virus-2 (SARS-Cov 2), began as an outbreak of pneumonia in Wuhan, China, in late December 2019, and quickly spread worldwide. It quickly escalated into an international public health crisis. This opened up the high demand for the innovation and research of new materials in the Personal Protective Equipment industry.

PubMed, Embase and Google Scholar were searched for relevant literature regarding personal protective equipment and the information was organized in a systematic way.

There are no adequate number of studies taken up in the field of use of textiles in medical applications especially with PPEs.

This structured review will generate a sense of the significance of using PPE for controlling pandemics and also awaken need for additional research and innovations in this area.

The authorities of the management should take timely intervention in choosing the right material for their PPE in their hospitals. Hence health care professionals teams have an inevitable role in preventing the adverse environmental impact due to the inadvertent disposal of PPEs.

There is a lack of systematic way of disposing contaminated single-use face masks in a safe, environmentally acceptable manner. The dumping of single-use PPE in domestic garbage has had an adverse effect on the environment. Mismanaged plastic waste endangers the health of ecosystems by polluting marine and terrestrial environments, posing a significant risk of ingestion or injury to animals and contaminating habitats.

This review article provides an in-depth review of the use of different materials in PPE and challenges regarding its long-term use and implications on the environment.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.

The study aims to explore and classify the key enablers of the Association to Advance Collegiate Schools of Business (AACSB) implementation in business schools.

By applying the Interpretive Structural Model (ISM) approach, it builds a hierarchical model of the identified enablers of AACSB implementation. Additionally, the Fuzzy Matriced Impacts Croises-Multiplication Applique and Classement (FMICMAC) technique is used to classify and determine the influence of these enablers on the implementation of AACSB accreditation.

The paper presents an ISM model of the identified enablers and draws managerial insight from it. Categorization of the key enablers into four groups helps in understanding the relative influence of each group of enablers on the AACSB implementation in business schools.

The proposed model of the key enablers will help business schools that are pursuing AACSB accreditation prioritize the enablers. As the study has considered experts' opinions to establish the model, some amount of bias cannot be discounted.

The development of the ISM model of the key enablers of AACSB implementation in business schools is a unique attempt. The findings will help business schools focus on the key enablers that influence implementation of AACSB standards.

This paper aims to evaluate the progress made in achieving sustainable development goal-2 (SDG 2) in India, with a focus on ending hunger, ensuring food security, improving nutrition and promoting sustainable agriculture. The assessment uses data from SDG Index reports, which offer a comprehensive overview of the advancements made by 28 states and 8 union territories (UTs) in India.

The evaluation is based on information derived from three editions of the SDG Index reports, initially published in 2018 and subsequently in 2019 and 2020. These reports provide a detailed analysis of the status and achievements of different states and UTs in relation to SDG 2. The categorization of states and UTs into aspirant, performer, front runner and achiever categories serves as a crucial framework for assessing the progress.

Despite concerted efforts by India, the majority of states and UTs are positioned in the aspirant and performer categories, suggesting that significant challenges persist in achieving SDG 2 targets. The results emphasize the necessity for stronger measures to elevate states and UTs to the categories of front-runners and achievers. The persistent challenges of malnutrition, hunger and their economic ramifications require immediate and strategic interventions to address these pressing concerns.

This paper contributes to the existing literature by providing a comprehensive analysis of the progress towards SDG 2 in India, using the insights from the SDG Index reports. The categorization framework used in this assessment offers a nuanced understanding of the challenges faced by different regions, highlighting the original contribution of this study. The findings underscore the urgency of targeted efforts to address malnutrition, hunger and related issues, emphasizing the importance of sustained commitment to achieving SDG 2 for the overall well-being of vulnerable populations.

This study aims to investigate the factors influencing the adoption of cloud accounting (CA) in Oman’s small and medium enterprises (SMEs). The research model is developed based on relationships between technology, organisational and environmental contexts.

This study used a questionnaire to collect data from a sample of SMEs in Oman’s information and communication sector. In total, 300 enterprises were selected, and the questionnaire was distributed to the executives. The questionnaires valid for analysis were 159. The collected data were analysed using structural equation modelling through analysis of a moment structures software.

This study tested seven factors, namely, support from top management, firm size, infrastructure (technology readiness), security and privacy, compatibility, competitive pressure and relative advantage. The results revealed that compatibility has a significant impact on the adoption of CA.

This study suggests the mangers in SMEs should play a more decisive role in identification of technological, organisational and environmental factors that affect the success of implementing CA in a comprehensive model.

This study constitutes a management strategy that helps the enterprises in light of limited economic resources and concerns about the use of cloud services to make the appropriate decision in adopting CA.

The purpose of this study is to capture patients' and employees' perception of quality of care in the Indian private hospitals and to find the possible perceptual gaps between both the groups.

Authors have referred to the Victorian patient satisfaction monitoring (VPSM) scale and studied the responses of 327 patients and 327 employees collected from six private Indian tertiary care hospitals. SPSS v26 software was used to conduct the data reliability test, descriptive analysis and Mann–Whitney U test.

Authors have found significant differences in perceptions of quality of care between the patients and employees in the Indian hospitals. Employees have high positive perceptions towards the provided medical care whereas the patients have less favourable perceptions for many quality indicators.

This study findings help the healthcare managers, practitioners and healthcare workers of the Indian hospitals to understand the perceptions of both the employees and the patients towards healthcare quality elements and help to reduce the existing perceptual gap in the process of providing quality healthcare services.

To the best of authors knowledge, this is one of the pioneering studies conducted in Indian healthcare industry to capture and compare the perceptions of both the employees' and the patients' perceptions of various quality of care elements. This study highlighted the existing perceptual gap between the employees and the patients on various healthcare quality elements and indicated the critical areas for improvement to provide high quality healthcare services.

Research of currently limited literature sees Robotic Process Automation (RPA) as an important tool at the tactical level. However, the literature has not considered its potential contribution to creating competitive advantages. This paper aims to link RPA and Resource-based view (RBV) literature, proposing a conceptual framework boosting RPA research as part of an organizational AI strategy.

This study applied a Systematic Literature Review (SRL), combining bibliometrics and content analysis. This study also built a new framework based on the updated RBV model that was transformed based on the RPA literature review results.

By bridging the two bodies of literature on RBV and RPA, this study manages to show the strategic side of the technology. Therefore, this study brought to light the most updated fundamental concepts of complementarity and scale-free fungible resources from RBV theory and AI technologies, applied to the domains of RPA, information systems and information technology (IS/IT) through the development of a new theoretical lens. Also, this study was able to elaborate on a new conceptual framework for AI strategy formulation to help organizations on their journey to AI utilization.

The authors did not find any research that has shown the strategic side of RPA, nor any that has used a theoretical lens based on the RBV theory to show this side. To the best of the author’s knowledge, this study seems to be the first to make the case for RPA's strategic potential.