Dr Abhijit Sengupta is a Reader in Business Analytics in the Department of Business Transformation at Surrey Business School. He holds a PhD in Economics from Stony Brook University in New York, an MA in Economics from Jawaharlal Nehru University, India and a BSc in Economics from University of Calcutta, India. He specializes in the use of advanced quantitative methods, including econometrics, machine learning and agent based simulations, and has experience of research in both academic and industrial settings.
Abhijit's current research interests are in the areas of innovation and technology management, global strategy and complex systems modelling. He has published in leading ABS 4 and 3 journals such as Research Policy, British Journal of Management, Journal of World Business, Journal of Economic Dynamics and Control, among others.
Previous to joining Surrey, Abhijit has worked in University of Kent (Senior Lecturer) and University of Essex (Lecturer and Senior Lecturer). Prior to academia, he worked in Unilever Research & Development, where he held posts of a Research Scientist and subsequently of a Senior Scientist. While in Unilever, he was part of and led multiple projects on price optimization, consumer behaviour analytics, brand competition strategy among others, working closely with multiple business functions.
Further details and a full CV can be found in Abhijit's personal website (link above under contact details).
Areas of specialism
Business, industry and community links
Abhijit is interested in supervising PhD students interested in undertaking research in the following areas:
- Knowledge exchange and technology transfer between universities and external stakeholders (industry, policy makers, charities etc.).
- Internationalization strategies of organizations, impact of innovation and R&D on such strategies in the medium to long run.
- Complex systems dynamics, behaviour over networks, of individuals, households and organizations.
He is keen to supervise students who are inclined towards quantitative research, using advanced quantitative methods. Qualitative or mixed methods approaches will be considered only under highly exceptional circumstances.
In the media
Innovation and Technology Management
University-Industry knowledge transfer and mechanisms
Innovation under public sector initiatives
Innovation and technology management in SMEs
Internationalization, Regionalization, R&D Management
Regionalization strategy among MNEs
Emerging market MNEs and internationalization strategy
Networks and Complex Systems
Dynamics of behaviour over networks
Market dynamics and evolution of firm behaviour
Interventions in social network and behaviour change
Principal Investigator. Society for Research in Higher Education Research Award 2017. Co-Investigator: Dr Federica Rossi (Birkbeck). Funded amount: £10,000.
Principal Investigator. British Academy Leverhulme Small Grants Award 2017 SRG171077. Funded amount £9790. Work ongoing.
Principal Investigator. The Vice Chancellor's Office, University of Essex. Funded amount: £10,000.
Principal Investigator. JNU-Essex Development Fund (JEDF) 2013. Funded amount: £5000.
Completed postgraduate research projects I have supervised
Dr Sengupta has supervised 3 PhDs to completion:
Tianchen Li, Essex Business School (PhD in Entrepreneurship, 2017), Entrepreneurship and environments: Start-ups, growth aspirations, and exit.
Anupriya Mishra, Essex Business School (PhD in Business Analytics, 2020), Entrepreneurship in the Rural Labour Market: An Agent-Based Modelling Approach.
Isha Mishra, Essex Business School (PhD in Business Analytics, 2020), Skills Mismatch in the Labour Market: An Agent-Based Modelling Approach.
He welcomes PhD applications in areas aligned to his research interests (innovation, internationalization, complex systems). He is keen to supervise students who are inclined towards quantitative research, using advanced quantitative methods. Qualitative or mixed methods approaches will be considered only under highly exceptional circumstances.
Postgraduate research supervision
On going PhD supervision:
- Koushik Das Sarma, Essex Business School, University of Essex. (External)
Abhijit has experience of designing and leading Business Analytics programs and modules while at University of Essex, for both MSc and PhD offerings. Modules included Business Analytics for Managers and Entrepreneurs, Statistical Analysis and Forecasting, Game Theory for Managers.
Business Analytics modules included topics such as RegressGion, Classification, Decision Trees, Neural Networks, Clustering, Time Series analysis among others.
He has previously taught a wide variety of Economics modules - Business Economics (UG), Managerial Economics (PG), Game Theory (UG), Introduction to Microeconomics (UG), Economics of Regulation (UG Intermediate). He has also led the design of UG module International Trade and Finance at University of Kent.
Led modules such as Introduction to Strategy (UG), Entrepreneurial Finance (UG), and co-taught modules such as New Venture Creation, Supply Chain Management etc.
A behavioral model incorporating utility based rational choice enhanced with psychological drivers is presented to study a consumer goods market, characterized by repeat purchase incidences by households. The psychological drivers incorporate purchase strategies of loyalty and change-of-pace, which affect the choice set of consumer agents in an agent based simulation environment. Agent specific memories of past purchases drive these strategies, while attribute specific preferences and prices drive the utility based choice function. Transactions data from a category in a supermarket is used to initialize, calibrate and test the accuracy of predictions of the model. Results indicate that prediction accuracy at both macro and micro levels can be significantly improved with the incorporation of purchase strategies. Moreover, increasing the memory length beyond a certain limit does not improve predictions in the model, indicating that consumer memory of past shopping instances is finite and low and recent purchase history is more relevant to current decision making than the distant past.
A single item is sold to two bidders by way of a sealed bid second price auction in which bids are restricted to a set of discrete values. Restricting attention to symmetric pure strategy behavior on the part of bidders, a unique equilibrium exists. When following these equilibrium strategies bidders may bid strictly above or below their valuation, implying that the item may be awarded to a bidder other than the high valuation bidder. In an auction with two acceptable bids, the expected revenue of the seller may be maximized by a high bid level not equal to the highest possible bidder valuation and may exceed the expected revenue from an analogous second price auction with continuous bidding (and no reserve price). With three acceptable bids, a revenue maximizing seller may choose unevenly spaced bids. With an arbitrary number of evenly spaced bids, as the number of acceptable bids is increased, the expected revenue of the seller and the probability of ex post inefficiency both may either increase or decrease.
This paper models the coalition formation process among primates as a sequential game. The population consists of individuals having distinct social ranks which is determined by the individual’s resource holding potential. Each member of the population is interested in gaining access to a food resource, either individually or via a coalition. At any given stage of the game, a player can either propose a specific coalition or he can be proposed to in order to join one. Hence, the strategy of a player consists of a sequence of decisions regarding who to propose to for the formation of a coalition and which proposals to accept or reject. We derive the preferences of the players over the various coalition structures under the assumption that the probability of a coalition to obtain the resource is given by a logistic distribution as a function of relative strengths of the players. We show that, given the primates’ strategic behavior, a variety of different coalition structures can emerge in equilibrium.
An agent based behavioral model incorporating utility based rational choice enhanced with psychological drivers is presented to study a typical consumer market. The psychological drivers incorporate purchase strategies of loyalty and change-of-pace, using agent specific memory of past purchases. Attribute specific preferences and prices drive the utility based choice function. Transactions data is used to calibrate and test the model. Results indicate that prediction accuracy at both macro and micro levels can be significantly improved with the incorporation of purchase strategies. Moreover, increased agent memory does not improve predictions in the model beyond a threshold, indicating that consumer memory of past shopping instances is finite and recent purchase history is more relevant to current decision making than the distant past. The article illustrates the use of agent based simulations to model changes or interventions in the market, such as new product introductions, for which no past history exists.
Brand competition is modelled using an agent based approach in order to examine the long run dynamics of market structure and brand characteristics. A repeated game is designed where myopic firms choose strategies based on beliefs about their rivals and consumers. Consumers are heterogeneous and can observe neighbour behaviour through social networks. Although firms do not observe them, the social networks have a significant impact on the emerging market structure. Presence of networks tends to polarize market share and leads to higher volatility in brands. Yet convergence in brand characteristics usually happens whenever the market reaches a steady state. Scale-free networks accentuate the polarization and volatility more than small world or random networks. Unilateral innovations are less frequent under social networks.
Emerging and developing countries are characterized by severe information asymmetries in knowledge markets, which when combined with other institutional weaknesses, leads to very low levels of interactions between universities and industry. Using data from a sample of Indian universities, we identify university specific publicly available organizational characteristics which, acting as " signals " , may reduce the information asymmetry problem and catalyze knowledge exchange (KE) partnerships. We find that strength of passive signals such as university ownership structure and reputation, and active ones such as volume of patents filed, impacts a university's KE performance positively. The impact of each signal is very KE channel specific, and the magnitude of this impact is large. We also find that signal strength negatively moderates the direct linkage between research and KE, implying that signaling is more relevant for universities where there is greater separation of its research outputs and KE performance.
In this contribution we aim at anchoring Agent-Based Modeling (ABM) simulations in actual models of human psychology. More specifically, we apply unidirectional ABM to social psychological models using low level agents (i.e., intra-individual) to examine whether they generate better predictions, in comparison to standard statistical approaches, concerning the intentions of performing a behavior and the behavior. Moreover, this contribution tests to what extent the predictive validity of models of attitude such as the Theory of Planned Behavior (TPB) or Model of Goal-directed Behavior (MGB) depends on the assumption that peoples’ decisions and actions are purely rational. Simulations were therefore run by considering different deviations from rationality of the agents with a trembling hand method. Two data sets concerning respectively the consumption of soft drinks and physical activity were used. Three key findings emerged from the simulations. First, compared to standard statistical approach the agent-based simulation generally improves the prediction of behavior from intention. Second, the improvement in prediction is inversely proportional to the complexity of the underlying theoretical model. Finally, the introduction of varying degrees of deviation from rationality in agents’ behavior can lead to an improvement in the goodness of fit of the simulations. By demonstrating the potential of ABM as a complementary perspective to evaluating social psychological models, this contribution underlines the necessity of better defining agents in terms of psychological processes before examining higher levels such as the interactions between individuals.
The volatility in a CPG market is modeled using a bottom-up simulation approach and validated against disaggregated supermarket transactions data. The simulation uses independent agents, each agent representing unique households in the data. A simple behavioral model incorporates household preferences for product attributes and prices. Our validation strategy tests the model predictions at both macro and micro levels and benchmarks the performance in each against a random choice model. The model significantly outperforms the benchmark at both levels. At the macro level, choices made by heterogenous agents accurately captures the volatility in market shares over time. This accuracy at the macro level is driven by the accuracy of predictions at the micro household level SKU and attribute choice.
This paper explores the impact of regional and firm level heterogeneity on MNE performance from an operational perspective. We find that the underlying economic growth of a region and the MNE’s overall product diversity significantly impact returns from downstream operations in specific regions. Based on a 10 year panel dataset of 1249 US based MNEs, results show that the incremental impact of the degree and speed of operations within a given region, is greater for regions exhibiting faster economic growth than for slower growing ones. For slower growing regions only, product diversity of the MNE becomes important and negatively moderates the link between operations and performance. Previous literature has shown that MNEs largely follow a regional strategy and has ignored the role of inter-regional differences, and how firm level characteristics interact with region specific ones. Once inter-regional heterogeneity is introduced, a more complex picture of the internationalization performance link emerges than has been addressed previously, with significant implications for the theory and practise of internationalization.
This paper addresses the gap in the knowledge transfer literature around how universities choose specific organizational models for their knowledge transfer offices (KTOs). Organization theory points towards strong interlinkages between strategy, structure and processes in organizations. This motivates an exploration of similar links within the organizational setup of KTOs. In doing so, the paper provides a unified theoretical framework around a university's choice of structure, business model and strategic preferences for their KTOs linked to university‐specific contextual factors. A qualitative approach is used wherein four very distinct British universities are examined as individual case studies. The authors find that strategic aims of the university around practitioner engagement, the quantity of applied research and research specialization are key factors in determining the organizational characteristics of the KTO. The theoretical framework derived from the cases makes two key contributions to the university knowledge transfer literature. First, it links the university‐level contextual factors to the local model of knowledge transfer. Second, it allows us to develop a set of generic models of knowledge transfer, which can potentially guide universities to develop their own specific models.
This paper examines the dynamic interlinkages between the two pillars of ambidexterity in universities, research and knowledge transfer. We propose a theoretical model linking these two pillars at the organisational level. The model is tested using the longitudinal HE-BCI survey data juxtaposed against two consecutive rounds of research evaluation in the UK higher education sector. Results indicate that a university’s past performance along the research pillar strengthens the knowledge transfer pillar over time, through both commercialisation and academic engagement channels. This positive impact is negatively moderated by the university’s size and reputation, in the sense that in larger or more reputed universities, the marginal impact of research on knowledge transfer declines significantly. Additionally, we find that knowledge transfer reinforces the research pillar through positive mediation between past and future research, but only through academic engagement channels. The results also indicate that contract research routes provide the maximum benefit for most universities in enhancing their ambidexterity framework, both in the short and the long run. For the relatively more reputed universities, it is the collaboration route which provides the maximum benefit. Interestingly, no such reinforcement could be detected in the case of the research commercialisation channels.
Recent research shows that because they rely on separate goals, cognitions about not performing a behaviour are not simple opposites of cognitions about performing the same behaviour. Using this perspective, two studies (N = 758 & N = 104) examined the psycho-social determinants of reduction in resource consumption. Results showed that goals associated with reducing versus not reducing resource consumption were not simple opposites (Study 1). Additionally, the discriminant validity of the Theory of Planned Behaviour constructs associated with reducing versus not reducing resource consumption was demonstrated (Study 1 & 2). Moreover, results revealed the incremental validity of both Intentions (to reduce and to not reduce resource consumption) for predicting a series of behaviours (Study 1 & 2). Finally, results indicated a mediation role for the importance of ecological dimensions on the effect of both Intentions on a mock TV choice and a mediation role for the importance of non ecological dimensions on the effect of Intention of not reducing on the same TV choice. Discussion is organized around the consequences, at both theoretical and applied levels, of considering separate motivational systems for reducing and not reducing resource consumption.
We consider a Cournot oligopoly market of firms possessing increasing returns to scale technologies (which may not be identical). It is shown that an external regulating agency can increase total social welfare without running a deficit by offering to subsidize one firm an amount which depends on the output level of that firm and the market price. The firms bid for this contract, the regulator collects the highest bid upfront and subsidizes the highest bidding firm. It is shown that there exists a subsidy schedule such that (i) the regulator breaks even, (ii) the subsidized firm obtains zero net profit and charges a price equal to its average cost, (iii) every other firm willingly exit the market and (iv) market price decreases, consumers are better off and total welfare improves.
Results from two studies on longitudinal friendship networks are presented, exploring the impact of a gratitude intervention on positive and negative affect dynamics in a social network. The gratitude intervention had been previously shown to increase positive affect and decrease negative affect in an individual but dynamic group effects have not been considered. In the first study the intervention was administered to the whole network. In the second study two social networks are considered and in each only a subset of individuals, initially low/high in negative affect respectively received the intervention as ‘agents of change’. Data was analyzed using stochastic actor based modelling techniques to identify resulting network changes, impact on positive and negative affect and potential contagion of mood within the group. The first study found a group level increase in positive and a decrease in negative affect. Homophily was detected with regard to positive and negative affect but no evidence of contagion was found. The network itself became more volatile along with a fall in rate of change of negative affect. Centrality measures indicated that the best broadcasters were the individuals with the least negative affect levels at the beginning of the study. In the second study, the positive and negative affect levels for the whole group depended on the initial levels of negative affect of the intervention recipients. There was evidence of positive affect contagion in the group where intervention recipients had low initial level of negative affect and contagion in negative affect for the group where recipients had initially high level of negative affect.
The special issue focuses on the theory and evidence linking the use of Big Data related technologies by businesses with their performance. Here we connect the papers accepted for the special issue to the overarching theme of Big Data as an emerging concept within the business management literature. We present two prominent case studies examining the use Big Data technologies on performance and strategy, followed by a discussion on how themes around Big Data and Performance may be examined from a theoretical perspective. Finally, based on a synthesis of papers in the current issue, we discuss the emerging issues and trends within the academic literature, relevant for future research.
This paper develops novel behavioural models of open innovation (OI) for competitive markets and uses them to compare the impact of two types of OI frameworks – open source (OS) and patent-licensing (PL). The dynamic consequences of OI, for both OS and PL, are studied using a complex adaptive systems approach. We examine how profits, technology levels, R&D investment, technology adoption and market structure evolve under each and are impacted by underlying market characteristics. While both OS and PL are found to be equivalent in technology outcomes, OS comes with additional advantages to participating firms. Firms in the OS framework earn higher profit and are more efficient with their R&D investments. The industry is less concentrated under OS than under PL, except when market size is very large. In both frameworks, consumer preference for new product adoption has a significant impact. When consumers adopt newly introduced products relatively quickly, market concentration is the higher and overall rate of technological progress slower. These results contribute towards a deeper theoretical understanding of OI, opening new avenues for future research.
High penetration of distributed technologies would call for a different way to manage electricity reliability for semi-independent households. One option could be to allow customers to withdraw power from the grid when their home system fails. This behavior, however, could constitute an existential threat for utilities: if consumers use the network less, and continue to pay according to their usage, the utility might be unable to recover its costs. This paper investigates whether the creation of a reliability insurance market would help to deal with these concerns. We propose a business model where utilities offer insurance to semi-independent, yet risk averse households, against the prospect of a blackout, when a pay as you go system is no longer available. With the use of an Agent Based Model, we test if contracts from this market can converge into a theoretical optimal contract where bounded perception of risks and losses impact the price of insurance and potential revenues of utilities. We find that such a market could exist as consumers efficiently transfer all or a portion of their risk to the utility, based on their willingness to pay and risk profiles, which allows them to avoid blackouts at the margin.
“Dynamics of Knowledge Exchange: Why and how do universities diversify or specialize?” SRHE Research Report, October 2019.
"Using Insurance to Manage Reliability in the Distributed Electricity Sector: Insights from an Agent Based Model". Discussion Paper, Kapsarc: Electricity Sector Transitions, July 2019.
"A Dual View of University-Industry Engagement in the UK: A Study of the Drivers and Models of Knowledge Transfer in UK Universities". Project Report from JNU-Essex Development Fund grant. University of Essex, April 2015.
“Economic Impact of University of Essex on the Local, Regional and National Economy”. Vice Chancellor's Office, University of Essex, 2015.
Conference Proceedings (since 2012)
"Beyond the Internationalization-Performance Relationship: Institutional Asymmetries and Complexity", Academy of Management (AOM) Proceedings, 2019, Boston, USA.
"Moving Beyond the Internationalization-Performance Relationship: Emerging Complexity, Institutional Asymmetries and Regional Dyads", Academy of International Business (AIB), 2019, Copenhagen, Denmark.
"Does Signaling Matter for Knowledge Exchange in Emerging Economies? A Study of Indian Universities", XVI Triple Helix Conference, 2018, Manchester, United Kingdom.
“Does distance matter? Impact of geographic and product diversification and their speeds on performance”, Strategic Management Society (SMS) Annual Conference, October 2017, Houston, USA.
“Interventions in social networks”, Conference on Complex Systems (CCS) 2015, Arizona, USA.
"Open innovation dynamics and comparisons with patent licensing”, Social Simulation Conference 2015, Groningen, The Netherlands.
“Dynamics of Technology Diffusion under Sequential Innovation”, Computational Economics and Finance, CEF 2014, Oslo, Norway
“Dynamics of Technology Diffusion under Sequential Innovation”, 3rd SKIN Workshop on Innovation and Complex Systems, Budapest, Hungary, 2014
Optimal Intellectual Property Protection under Sequential Innovation”, European Social Simulation Association (ESSA) Conference 2013, Warsaw, Poland, 2013
"Social Simulation with the Consumer Goods Industry - The Way Forward" Proceedings of the 26th European Conference on Modelling and Simulation (ECMS 2012), Koblenz, Germany, 2012.