Indian Institute of Management Ahmedabad

About: Indian Institute of Management Ahmedabad is a education organization based out in Ahmedabad, India. It is known for research contribution in the topics: Emerging markets & Population. The organization has 1828 authors who have published 4011 publications receiving 59269 citations. The organization is also known as: IIMA & IIM Ahmedabad.

Personal Characteristics and Job Satisfaction: India-Nigeria Comparison

Abstract: This study examines the relationship between job satisfaction and personal characteristics on samples of 778 Indians and 620 Nigerians. The results indicate no relationship between sex, marital status, and annual income and job satisfaction for both the samples. Age showed quadratic and linear relationship with satisfaction for Indian and Nigerian samples respectively. Satisfaction increased with increasing number of dependents and work experience and decreased with increasing years of education for both the samples. The regression analysis showed that all seven personal characteristics accounted for 34.9 per cent and 71.7 per cent variation in job satisfaction for Indian and Nigerian employees, respectively. Culture and level of industrialization have been examined to explain the differences in the results.

An Optimization-Based Decision Support System for Strategic and Operational Planning in Process Industries

Abstract: We describe how a generic multi-period optimization-based decision support system can be used for strategic and operational planning in process industries. Built on five fundamental elements—materials, facilities, activities, time periods and storage areas—this system requires little direct knowledge of optimization techniques to be used effectively. Results based on real data from an American integrated steel company demonstrate significant potential for improvement in revenues and profits.

Issues and Concerns in the Implementation and Maintenance of HRIS

Abstract: This article looks at the issues and concerns faced by nine Indian organisations in implementing and managing Human Resource Information Systems (HRIS). The organisations are diverse in terms of size and sector that they belong. The critical success factors and weaknesses in various stages of implementing an HRIS are explored in this paper. The problems are rooted in mainly two factors. One is the fact that the HR department lacks knowledge about HRIS and hence is not able to clearly elucidate the requirements of the system. Poor need assessment is a continuation of this problem. Second is the lack of importance given to the HR department in the organisations.The spectrum of cases covered shows the clear variation in terms of the success of implementation. In poorly managed implementations, the potential of HRIS has been under-utilised. Only a few modules have been implemented and at best HRIS's role is that of a centralised database. Very high dependence is placed on the vendors without having a clear id...

Utilizing emotion scores for improving classifier performance for predicting customer's intended ratings from social media posts

Abstract: Social media channels provide an avenue for expressing views about different services/products. However, unlike merchandise/company websites (where users can post both reviews and ratings), it is not possible to understand user's ratings for a particular service-related comment on social media unless explicitly mentioned. Predicting ratings can be beneficial for service providers and prospective customers. Additionally, predicting ratings from a user-generated content can help in developing vast data sets for recommender systems utilizing recent data. The aim of this study is to predict ratings more accurately and enhance the performance of sentiment-based predictors by combining it with the emotional content of textual data.,This study had utilized a combination of sentiment and emotion scores to predict the ratings of Twitter posts (3,509 tweets) in three different contexts, namely, online food delivery (OFD) services, online travel agencies (OTAs) and online learning (e-learning). A total of 29,551 reviews were utilized for training and testing purposes.,Results of this study indicate accuracies of 58.34%, 57.84% and 100% in cases of e-learning, OTA and OFD services, respectively. The combination of sentiment and emotion scores showed an increase in accuracies of 19.41%, 27.83% and 40.20% in cases of e-learning, OFD and OTA services, respectively.,Understanding the ratings of social media comments can help both service providers as well as prospective customers who do not spend much time reading posts but want to understand the perspectives of others about a particular service/product. Additionally, predicting ratings of social media comments will help to build databases for recommender systems in different contexts.,The uniqueness of this study is in utilizing a combination of sentiment and emotion scores to predict the ratings of tweets related to different online services, namely, e-learning OFD and OTAs.