Manoj Kumar Jha

Understanding and predicting the determinants of cloud computing adoption: A two staged hybrid SEM - Neural networks approach

Along with water, gas, electricity, and telephone, cloud computing has been considered as the fifth utility. Like other utility services available in todays social computing services are readily available on demand (Buyya, Yeo, Venugopal, Broberg, & Brandic, 2009). The purpose of the study is to develop a hybrid two-stage, structural equation modeling (SEM) artificial neural network (ANN) model to predict motivators affecting cloud computing adoption services in the Indian private organizations. This research article proposes a new paradigm by extending the Technology Organization Environment Model (TOE) with external factors, namely, perceived IT security risk and risk analysis for the first time in a technology adoption study. One of the core contributions of the study is the introduction of new factors, perceived IT security risk and risk analysis. Data were collected from 660 professional experts and analyzed using structural equation modeling (SEM) and artificial neural network (ANN) modeling. The SEM results showed that perceived IT security risk (PITR), risk analysis (RA), technology innovation (TI), management style (MS) and trust (T) have a significant influence on cloud computing adoption. The only exceptions were the usage of technology (UT) and industry usage (IU) which witnessed statistically insignificant influence on cloud computing adoption. Furthermore, the results obtained from SEM were employed as input to the artificial neural network (ANN) model and results showed that trust, perceived IT security risk, and management style as most important predictors in cloud computing adoption. To develop a hybrid two- stage model, SEM ANN model.Proposes a new model by extending the TOE model with external factors.Data were collected from 660 professional experts.Analyzed using SEM and ANN modeling.

Selection and evaluation of third party logistics service provider (3PLSP) by using an interpretive ranking process (IRP)

Purpose The concept of third-party logistics service provider (3PLSP) has been considered as an essential organizational philosophy to achieve profits. The purpose of this paper is to analyze and examine the contextual relationship among the critical success factors (CSF) of 3PLSPs practices in the cement manufacturing industry. Design/methodology/approach In this paper, the total 20 critical selection criteria with nine processes for the 3PLSPs, of an Indian cement manufacturing industry have been identified through an exhaustive literature review and opinions of the experts i.e. academics and industries. Interpretive ranking process (IRP) methodology has been presented to find out the rankings of the individual criteria and the mutual influence in the selection process. Findings The proposed model establishes the dominance of relationship among identified criteria, which plays a vital role in the 3PLSPs selection process which are experience in similar product, quality of management, information technology capacity, flexibility in operation and delivery, compatibility with the users. Research limitations/implications An empirical research approach has not been used to collect primary data to rank different criteria for effective 3PLSPs implementation in the Industry. In this paper, an example of Indian cement industry is presented to show the real world applicability of the proposed model. Originality/value This model would help a decision maker to decide the issues related to a selection of 3PLSPs. The third party service provider comprises the use of external companies who controls and delivers logistic activities. The paper discusses very practical issues in an analytical manner, using the case base method.

Risk analysis in adoption of cloud computing in SMEs - a literature review

This paper presents a systematic literature review, to explore the current key issues related to cloud computing adoption in small medium enterprises SMEs. This is achieved by reviewing 55 articles published about cloud computing adoption in SMEs. Using the grounded review approach, articles are classified into four main categories: Cloud computing; adoption of cloud computing; adoption of cloud computing in SMEs; risk analysis in adoption of cloud computing in SMEs. Then, the four categories are divided into one focus abstract: risk analysis in adoption of cloud computing in SMEs, where the former affects the latter. The results of this review indicate that enterprises face serious problems after implementation of cloud computing with respect to risk. Based on the findings, the paper provides a future research agenda to explore the previously under-investigated areas regarding cloud computing adoption factors and processes. This paper calls for further theoretical, methodological, and empirical contributions to the research area of cloud computing adoption in SMEs. It provides a comprehensive view of insights gained in this area of research through the bibliography.

To identify the critical success factors for cloud computing adoption by MCDM technique

SMEs play a very vital role in each market by significantly contributing to each countrys gross domestic product (GDP) and labour market. Therefore, proposing new strategies or developing new systems that can help SMEs become more efficient and productive is not only beneficial for SMEs but also for the economy of a country as a whole. The decision about cloud computing adoption is crucial for every manufacturing firm. However, the selection on an appropriate system may prove difficult, especially for small and medium manufacturing enterprises which may not have sufficient economic and human resources to properly implement the system. The present study aims to provide a systematic approach towards the cloud computing adoption. It is worth noting to determine the decisive factors in adoption of cloud computing adoption and to weight them. In this paper, analytic hierarchy process (AHP) is applied to find the importance degree of each criterion and as the measurable indices of the cloud computing adoption. This study considers nine criteria with 51 sub-criteria, which has somewhat already been used, and establishes a ranking model that provides decision makers to assess the factors prior the adoption of cloud computing.