Amitrajit Sarkar

Bio: Amitrajit Sarkar is an academic researcher from Ara Institute of Canterbury. The author has contributed to research in topics: Resilience (network) & Conceptual framework. The author has an hindex of 5, co-authored 14 publications receiving 62 citations.

Towards Golden Rule of Capital Accumulation: A Genetic Algorithm Approach

Abstract: The current study deals with maximizing consumption per worker in connection with the economic growth of society The traditional Solow model based approach is well-studied and computationally complex The present work proposes a Genetic Algorithm (GA) based consumption maximization in attaining the Golden rule An objective function derived from traditional Solow model based on depreciation rate and amount of accumulated capital is utilized The current study considered a constant output per worker to incorporate a constant efficiency level of labor Different ranges of Depreciation rate and accumulated capital are tested to check the stability of the proposed GA based optimization process The mean error and standard deviation in optimization process is utilized as a performance metric The experimental results suggested that GA is very fast and is able to produce economically significant result with an average mean error 0142% and standard deviation 0021%

CEO Decision Making under Crisis: An Agency Theory Perspective

Abstract: Organisational resilience has gained increasing attention in recent years. This paper focuses on information systems resilience, which is an aspect of organisational resilience. Given the potentially devastating implications of disruptions to organisations, understanding the dynamics of the successful adaption of IS within organisations indicates an important avenue for future research. In this paper, we adopt Agency Theory to develop a conceptual framework, focused on decision making and planning for IS resilience. Concourse theory and Q-methodology were used to develop a Q-sort questionnaire, which was refined through interviews with researchers and IS professionals. The resulting 37 statements were then sorted by eight CEOs of Small Medium Enterprises (SME). Q-sort methodology identified three types of decision makers from the data, each representing distinct collective perspectives. These types are described and discussed, along with implications of findings as well as suggestions for future research.

Organisational IS resilience: a pilot study using Q-methodology

Abstract: Organisational resilience has gained increasing attention in recent years. This paper focuses on an aspect of organisational resilience, i.e., on IS resilience. Given the potentially devastating implications of disruptions to organisations, understanding the dynamics of the successful adaption of IS within organisations indicates an important avenue for future research. In this paper, we adopt Agency theory to develop a conceptual framework, focused on decision making and planning for IS resilience. Concourse theory and Q-methodology were used to develop a Q-sort questionnaire, which was refined through interviews with researchers and IS professionals. The resulting 38 statements were then sorted by eight managers. Q-sort methodology identified three types from the data, each representing distinct collective perspectives. These types are described and discussed, along with implications of findings as well as suggestions for future research.

Share Market Sectoral Indices Movement Forecast with Lagged Correlation and Association Rule Mining

Abstract: This paper analyses the correlation between two different sectoral indices (eg between Automobile sector index and between Metal sector index, between Bank sector index and IT sectoral index etc) in a time lagged manner Lagging period is varied from 1 day to 5 days to investigate if any selected sector has lagged influence over any other sectoral index movement If any upward/downward movement of a sectoral index (sector A) is correlated with similar upward/downward movement of another sectoral index (Sector B) with a time lag of ‘d’ days, then with association rule mining support and confidence is calculated for the combination If d is the lag for which support and confidence is maximum then depending on the higher correlation as well as higher support and confidence value it is possible to forecast future (d days ahead of current day) movement of sector B based on present day movement of sector A This model first uses correlational analysis to identify the level of dependence among two different sectors, then considers only those sectors having higher value of correlation for association rule mining Those sector are not considered for which combination correlation is very low or 0

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Abstract: How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

Doing Q-methodological research: theory, method and interpretation

Abstract: Q-methodology is a qualitative research technique designed to capture the subjective viewpoints of its participants. Doing Q-Methodological Research: Theory, Method and Interpretation sheds light o...

A 'conceptual models' approach to organisational resilience

Abstract: Gibson and Tarrant discuss the range of inter-dependant factors needed to manage organisational resilience Over the last few years there has been considerable interest in the idea of resilience across all areas of society Like any new area or field this has produced a vast array of definitions, processes, management systems and measurement tools which together have clouded the concept of resilience Many of us have forgotten that ultimately resilience is not just about ‘bouncing back from adversity’ but is more broadly concerned with adaptive capacity and how we better understand and address uncertainty in our internal and external environments The basis of organisational resilience is a fundamental understanding and treatment of risk, particularly non-routine or disruption related risk This paper presents a number of conceptual models of organisational resilience that we have developed to demonstrate the range of inter-dependant factors that need to be considered in the management of such risk These conceptual models illustrate that effective resilience is built upon a range of different strategies that enhance both ‘hard’ and ‘soft’ organisational capabilities They emphasise the concept that there is no quick fix, no single process, management system or software application that will create resilience