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Given the competitive landscape in the higher education setting, it is important that universities adopt strategies that create competitive advantage for them. Universities must leverage their resources efficiently to address this goal. Creating a positive brand image is one such strategy. The purpose of this paper is to conceptualize university brand image as its heritage, service quality and trustworthiness and investigate their relationship with student’s satisfaction. It also investigates the role of university reputation as a mediating variable.

Data were collected through a mixed method approach. The first stage involved qualitative interviews and focused group discussions with students to understand the factors responsible for student satisfaction with their respective universities. The second stage involved administering a survey questionnaire in two geographies – the USA and India to investigate the hypothesized relationship. The authors use regression analyses to test these relationships.

Findings indicate that a distinct brand image plays an important role in students’ level of satisfaction across both the USA and India. Service quality has a greater impact on student satisfaction levels across both contexts (as compared to university heritage and trustworthiness). The authors also find a positive mediating effect of university reputation in the relationship between university brand image and student satisfaction levels.

The current research contributes to the services marketing literature in the university context. It offers a framework for decision making in universities. It suggests that universities must work toward developing their brand image by focusing on its three dimensions – heritage, trustworthiness and service quality.

The internal (farmer-controlled) and external (non-farmer-controlled) factors affect crop yield. However, not a single study has identified and analyzed yield predictors in India using effective predictive models. Thus, this study aims to investigate how internal and external predictors impact pearl millet yield and Stover yield.

Descriptive analytics and artificial neural network are used to investigate the impact of predictors on pearl millet yield and Stover yield. From descriptive analytics, 473 valid responses were collected from semi-arid zone, and the predictors were categorized into internal and external factors. Multi-layer perceptron-neural network (MLP-NN) model was used in Statistical Package for the Social Sciences version 25 to model them.

The MLP-NN model reveals that rainfall has the highest normalized importance, followed by irrigation frequency, crop rotation frequency, fertilizers type and temperature. The model has an acceptable goodness of fit because the training and testing methods have average root mean square errors of 0.25 and 0.28, respectively. Also, the model has R² values of 0.863 and 0.704, respectively, for both pearl millet and Stover yield.

To the best of the authors’ knowledge, the current study is first of its kind related to impact of predictors of both internal and external factors on pearl millet yield and Stover yield.

The literature reveals that most studies have estimated crop yield using limited parameters and forecasting approaches. However, this research will examine the impact of various predictors such as internal and external of both yields. The outcomes of the study will help policymakers in developing strategies for stakeholders. The current work will improve pearl millet yield literature.

The energy optimization techniques developed for conventional ad hoc networks do not appropriately address the unique features of the wireless embedded sensor networks (WESNs). In the WESN environment, only reducing the overall energy consumption is not considered enough to maximize the life span of the entire network, but maintaining full network connectivity for a sufficiently long period of time is also an important design goal due to the energy constraints of each node. The wireless radio is a major energy user and is often the focus of energy conservation mechanisms, since the nodes communicate in a shared medium (air interface). The medium access control (MAC) layer of the communication protocol stack arbitrates access to the communications link by manipulating the sleep, listen, transmit, and receive states of the radio transceivers. The bursty traffic networks experience long periods of inactivity interrupted by unplanned and often short lived periods of high traffic loads. Currently available MAC protocols cannot meet application fidelity requirements of the bursty traffic networks since they are designed either for networks with periodic traffic or are not sufficiently traffic-adaptive, thereby introducing large multi-hop latency delays to realize network connectivity, overprovision during light traffic conditions, and slow ramp up at the initiation of a high traffic episode. This paper presents enhancements made to the energy efficient MAC protocol which is especially designed for the bursty traffic networks and in the process targets some available communication techniques used in the WESNs for discussion and comparison.

Selection of logistics service provider (LSP) (also known as Third-party logistics (3PL) is a critical decision, because logistics affects top and bottom line as well. Companies consider logistics as a cost driver and at the time of LSP selection decision, many important decision criteria’s are left out. 3PL selection is multi-criteria decision-making process. The purpose of this paper is to develop an integrated approach, combining quality function deployment (QFD), and Taguchi loss function (TLF) to select optimal 3PL.

Multiple criteria are derived from the company requirements using house of quality. The 3PL service attributes are developed using QFD and the relative importance of the attributes are assessed. TLFs are used to measure performance of each 3PL on each decision variable. Composite weighted loss scores are used to rank 3PLs.

QFD is a better tool which connects attributes used in a decision problem to decision maker’s requirements. In total, 15 criteria were used and TLF provides performance on these criteria.

The proposed model provides a methodology to make informed decision related to 3PL selection. The proposed model may be converted into decision support system.

Proposed approach in this paper is a novel approach that connects the 3PL selection problem to practice in terms of identifying criteria’s and provides a single numerical value in terms of Taghui loss.

The introductory paper begins with the issue about the relevance of research in management. It emphasizes the need for scholars to adopt methodologies best suited to the research problem of their choice. This paper contains sections on the nature of management research, dominant research paradigms, the methodological domain, quantitative versus qualitative research, and triangulation in using multiple methodologies. The paper provides a background to the purpose of the book and summarizes in brief the purpose of each the subsequent papers.

To assess the state of supply chain management (SCM) research in India and to understand the research trends and methodologies used. The present study also aims to create a taxonomy of the subject areas researched in India.

The present study employed the systematic literature review methodology. Literature from 395 peer journal papers in 67 leading journals over a 20-year period (2000–2020 Quarter-1) was comprehensively reviewed and assessed.

SCM research in India started around the year 2000. The quantum of research was low (single digit) until 2010. There has been steady growth over the last decade, and over 50% of the total papers up until now has been published in the last four years. The present study created a three-tiered taxonomy of the subject areas and classified the papers as per it. The first tier (level-1) has seven categories (SCM strategy, network design, SCM processes and integration, IT systems, skills, performance measurement and others). A perusal of the newly created taxonomy revealed that, except for a few areas under level-1 categories (such as SCM processes and SCM strategy), the other level-1 categories have not seen much research. Similarly, there is little or no research in a large number of level-2 categories (such as outsourcing strategy, channel strategy, demand management, demand fulfillment, customer relationship management, integrated supply chain planning, new product development, returns, supply chain orientation, performance monitoring, performance improvement, SCM adoption process, SCM implementation issues and quantified benefits of SCM). Methodologically, the rigor of SCM research in India needs improvement.

A comprehensive taxonomy of SCM subject areas researched in India at three cascading levels was created for the first time in the present study. The taxonomy will help provide researchers with a clear understanding of the structure of the subject areas and help in identifying areas where research has been carried out and the subject areas where gaps exist for future research to proceed. The present study also provides an overview of the methodological rigor of SCM research in India and points out some of the limitations that researchers should avoid in future studies.

The risk factors associated with clients have a major impact on the successful delivery of a project from early design to the construction and operation stages. Risk management studies conducted so far have not succeeded in providing an effective risk assessment methodology for clients in analysing and managing the risk factors that cause both project delays and cost overruns. So, the purpose of this paper is to provide a methodology for a client-based risk management model.

A conceptual framework is designed by integrating the findings from a literature review and a construction industry survey in the Kingdom of Saudi Arabia. The framework includes the risk identification, risk analysis and mitigation strategy, which are the key components of the model. The model of the framework is developed by integrating the analytical hierarchy process (AHP) and Monte Carlo simulation (MCS) underpinned within an @Risk program.

A case study is used to demonstrate the proposed methodology; the results found that the model helps to analyse and quantify the impact of risk factors, and also to assist in taking a suitable risk mitigation strategy, particularly at the early design stage in the construction process.

The model is applicable to both public and private clients when they need to know the possible project duration in a new construction project, and to take some proactive actions to avoid the adverse effect of client risk factors at the early stage of the project.

The model is expected to help in understanding the nature, and analysing the influence, of client risk factors that cause project delays and cost overruns. The development of the methodology for managing the client-based risk in construction processes at the early design stage is the key value of the study.

The purpose of this paper is to investigate both long-run and short-run dynamics among the software and services export, investment in information technology (IT) and GDP in India and to investigate the direction of the relationship among the given three macro-economic variables.

The time series data have been taken to investigate the long-run relationship exists among the variables. Annual data were collected from the NASSCOM Annual Reports, Planning Commission of India and Reserve Bank of India during the period 1980–2016. Cointegration and vector error correction model have been used for analyzing the causal relationship among investment in IT, software exports and GDP in India.

Cointegration results confirm that software and services export, investment in IT and GDP are cointegrated, implying that there exists the long-run equilibrium relationship among the given three macro-economic variables. Similarly, vector error correction mechanism Granger causality results hold that there is uni-directional long-run causality running from software and services export and investment in IT to GDP, implying that software and services export is an important determinant of economic growth in India.

The limitations of the paper are generalization of the results and proxy variable for IT investments.

The paper has implications for the expansion of market concentration, diversification of software and service exports, and investments in R&D for increasing competitiveness of the industry in the global market.

This paper focuses on originality in the analysis of the relationship among the given variables software exports, investment in the IT sector and GDP in India. All the work has been done in original by the authors and the work used have been acknowledged properly.

The current study aims to investigate the existing relationship between knowledge management (KM) infrastructures, KM process capabilities, creative organizational learning (OL) and organizational performance.

Statistical population includes executives of knowledge-based companies in Tehran Science and Technology Park of Iran. The 68 questionnaires were distributed among the census, of which 60 questionnaires were completed correctly. The research data were analyzed by SPSS and PLS software. The unit of analysis is a company that has adopted a knowledge management system (KMS). Target population of the research consisted of 85 top managers of knowledge-based companies in Tehran Science and Technology Park of Iran (N = 85). Random sampling method was applied in this study, and 71 top managers were considered as the statistical sample based on the “Morgan Table”. One standard five-point Likert questionnaire was adopted and distributed between top managers in the park; 62 questionnaires were returned, among which 60 were statistically investigated. The structural relations among variables were tested using the partial least squares method.

This study shows that the KM processes can mediate between creative OL and factors in the KM infrastructure. The results of the study demonstrate that KM process capabilities have the most crucial role in creative OL. The results indicate a significant influence of the infrastructure capabilities on the process capabilities, also the impacts of KM process capabilities on creative OL and the impacts of creative OL on organizational performance was confirmed.

Using a holistic view of the KM performance framework, this study has provided insights to KM for researchers because it explains the integrated aspects of KM performance by examining the relationships between the KM infrastructure, knowledge process capabilities, and organizational outcomes. Previous studies on KM have been fragmented because they only consider some aspects of KM performance rather than using a holistic view of the KM performance framework: they have examined the relationship between one or two facets of KM enablers and process capability, or between KM process capabilities and organizational performance.

In order to manage rapid change and global competition in business environments, knowledge workers should create new business opportunities and continuously question what and how they can contribute to these chances. Organizational KMS should support the learning processes of their knowledge workers.

The continuous learning and experiments are necessary in order to produce new ideas and products: it is critical to emphasize the importance of a KM infrastructure that supports and encourages learning in organizations. The creative learning in turn affects organizational performance indicating that without learning, organizations cannot overcome the boundary of old business practices and adjust to change in environments.

Previous researches did not appraise the effect of KM and its capabilities on organizational performance, and the specific influence of creative OL was disregarded. The present study demonstrates the mechanism of KM effect on organizational performance and describes the comprehensive dimensions of KM performance.