| 1. |
- Aneja, Arun P., et al.
(författare)
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Ambidexterity drivers in plural business models’ (pBMs’) value-structure: an explorative study from DuPont
- 2016
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Ingår i: From Science to Society: Innovation and Value Creation. - University of Cambridge.
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Konferensbidrag (refereegranskat)abstract
- This paper investigates how can ambidexterity be detected and classified in plural business models (pBMs) at the level of their underlying value-structure (value- creation and extraction), and what are the drivers. Such pBMs are run by multi-national firms to accommodate various technologies and innovations however is stressful due to inherent incompatibilities and conflicts between them. Existing scholarly discussion is limited in exploring this issue, from a value generation perspective, essential to identify where to and how to commit resources in these pBMs. The paper builds upon an explorative study of six successful product cases (and their associated business models) from DuPont’s Textiles Fibre Division (DTFD) to show how exploration and exploitation generates resultant trajectories along value- creation and extraction mechanisms, respectively, in a product. Consistent and inconsistent combinations of these trajectories along the value-structure results in four differential drivers of pBMs, viz. (i) technological breakthrough, (ii) market-back technology, (iii) continuous technology, and (iv) continuous market-back, thus characterizing their inherent ambidexterity. These ambidexterity tendencies are along value- creation and extraction mechanisms.
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| 2. |
- Aneja, Arun, et al.
(författare)
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Textile Sustainability : Living Within Our Means
- 2015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Sustainability is defined by Brundtland as “….development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. An evaluation of the current ‘pulse of the planet’ which consists of nature’s core business of creating diversity, abundance and continuance yields a bleak future. It suggests limited supplies of natural resources that pose an obstacle to future worldeconomic growth. This paper makes an assessment of a sustainable future for textiles based on economic, social,and environmental dimensions. Both strategic and tactical remedies for the textile value chain are provided. Thecollective actions suggested will not ensure success but rather provide a framework for a better and safer planet.
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| 3. |
- Aneja, Arun, et al.
(författare)
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Textile Sustainability : Major Frameworks and Strategic Solutions
- 2015
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Ingår i: Handbook of Sustainable Apparel Production. - : CRC Press. - 9781482299373 ; , s. 289-306
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Bokkapitel (refereegranskat)abstract
- Sustainability is commonly defined as “….development that meets the needs of the present without compromising the ability of future generations to meet their own needs”. An evaluation of the current ‘pulse of the planet’ which consists of nature’s core business of creating diversity, abundance and continuance yields a bleak future. It suggests limited supplies of natural resources that pose an obstacle to future world economic growth. In this context, the work makes an assessment of a sustainable future for textiles and apparel industries based on economic, social, and environmental dimensions along the major emergent patterns highlighted in 8 critical sustainability frameworks (viz. ecological footprint, natural step, natural capitalism, industrial ecology, cradle-to-cradle, bio-mimetic, ZERI, and planetary boundaries). A fundamental mind-shift in these industries by identifying various components of non-sustainability is suggested. Such deeper insights and collective changes will not provide solutions to ensure success but rather provide a holistic and integrated systems perspective to give rise to this major transformation.
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| 4. |
- Aneja, Arun, et al.
(författare)
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Textile Thru the Looking Glass : A Novel Perspective
- 2013
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Today, textiles and fiber science in US, Europe and Japan from its once lofty perch in the global economy, stands in stark contrast to its preeminent position of few decades ago. Its influence on the society as a whole has eroded enormously. Many of the synthetic fiber products that once fuelled the rapid growth of the industry have become mature commodity products now characterized by low growth and lower profit margins. To add to the current dilemma, organizational ‘health’ and growth processes are constantly threatened in this era of turbulence. Thus the drive for survival and success has translated, in recent times, to quest for resiliency – to survive and thrive in turbulences. On the other hand, most managers and academicians agree that innovation ensures superior organizational performance while recent research has shown that most resilient companies can dynamically orchestrate diverse innovation strategies. Resiliency in such a context has become a prerequisite for a sustained long term business prosperity fuelled by diverse technological innovations. This has intensified the organization’s search for differentiated products and services, processes, business models, technology, strategies etc. pushing firms to gain competitive advantage and also to develop new knowledge and innovation performance to drive sustainable growth. Organizations now follow multiple innovation strategies to pragmatically devise their innovation repertoire for delivering growth, hence, success in turbulent times while emphasizing resiliency. What does the future hold and how can we reverse the trend to achieve and sustain the impressive credentials of the past? To understand the significance of what the future may hold, and to reverse the downward spiral of the industry, we must evaluate the successes and failures of the past and come to grips with rapid global changes and turbulences currently underway. The present article seeks to explore such an inexorable phenomenon of quantifying and correlating innovation and business resiliency over a time line, from the annual financial data of 35 healthy and unhealthy companies along with 5 textile companies over a span of few decades. These are then extrapolated with certain predictive capabilities to suggest future trends and strategies for the textile companies. Learning from these companies, if adopted, will yield capacity to transform the scenario. Assessments and classification of the economic health of a company is typically made based on some quantity derived from selected indices, such as Altman’s Z-score. These methods can describe an instantaneous status, or a “time snap” of an economical subject but lack information about the time-dynamics of the assessment, which is important for investors, shareholders and the management. We suggest using historical data to estimate current trends in the form of the first and second time-derivative of the appropriate quantity in the time domain. This new information is independent on the quantity itself and beside more precise description can be used as new predictor to improve effectiveness of classification of successful and unsuccessful subjects. This approach is further discussed in this paper.
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| 5. |
- Aneja, Arun, et al.
(författare)
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The Quest for Continual Growth in Textiles : Innovation Diversity and Organizational Resiliency
- 2012
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The brutally competitive nature globally and raw material volatility of textile industry are some of the reasons why companies cannot afford to fall behind in efficiency, innovation or organizational resiliency. The present article seeks to explore the common thread and textile-related scientific views that changed our lives through the ages. Who were the textile dream weavers and the companies that transformed our industry? In addition we explore how we can use the teachings of these lessons to build novel platforms for innovations in textiles for the future. Today, textiles and fiber science in US and Europe, from its once lofty perch in the global economy, stands in stark contrast to its preeminent position of just a decade ago. Its influence on the society as a whole has eroded enormously. Many of the synthetic fiber products that once fueled the rapid growth of the industry have become mature commodity products now characterized by low growth and lower profit margins. Intense global cost pressure, higher consumer expectations, a highly diverse customer base, shorter fashion cycles and reduced R&D spending have all contributed to the current malaise. What does the future hold and how can we reverse the trend to achieve and sustain the impressive credentials of the past? To add to the current dilemma, organizational ‘health’ and growth processes are constantly threatened in this era of turbulence. James Moore, in his book ‘The Death of Competition’ (1995) describes this dynamics as a ‘co-evolving’ one with unpredictable changes in markets, technology, workforces and organizations. Thus the drive for survival and success has translated, in recent times, to quest for resiliency – to survive and thrive in turbulences. On the other hand, most managers and academicians agree that innovation ensures superior organizational performance while recent research has shown that most resilient companies can dynamically orchestrate diverse innovation strategies. This has intensified the organization’s search for differentiated products and services, processes, business models, technology, strategies etc. pushing firms to gain competitive advantage and also to develop new knowledge and innovation performances to drive sustainable growth. This has resulted in organizations to follow multiple innovation strategies and to prudently devise their innovation repertoire for delivering growth, hence, success in turbulent times emphasizing resiliency. In this paper, authors diagnose an organization’s innovation in terms of the tendency to utilize its resources and dynamic capabilities, and streamline them along an ‘innovation topology’ viewed through a two dimensional matrix of (i) locus of development - innovation either internal or external to the organization, and (ii) change in performance - innovation either in use or being created newly. The portfolio of innovation strategies include sustaining innovation (internal) or through mergers and acquisitions (M&A)/joint ventures (JV) (by extending firm boundary) but using existing resources and capabilities in both cases; or radical/break-through innovations (creating new capacities internally) or disruptive/transformational innovation (exploring and creating new capacities beyond existing boundaries). A case study approach is adopted using Du Pont Company with its unparallel 200 years of ‘history of innovation and transformation’ for validating the proposed model. This is seminal from both business and academic theory-building perspective for devising unique innovation repertoire and organizational resiliency for continual growth.
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| 6. |
- Aneja, Arun, et al.
(författare)
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Towards a circular economy in textiles: RESYNTEX and the European Uniion
- 2016
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Ingår i: Fibres and Textiles (Vlákna a textil). - 1335-0617. ; 23:3, s. 15-21
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Europe is at crossroads in terms of growth and living standards. The nexus between circulareconomy, RESYNTEX and textile provides direction and opportunity for seamless prosperity. The currentstrategy consisting of a linear economy for resource utilization, a surprisingly wasteful model of valuecreation, is leading to decline in prosperity and concomitant global influence. It must develop a moreresource savvy circular economy, with the biological and mineral nutrients of modern society continuouslycirculating. Rather than face a bleak and uncertain future dependent on resources from overseas, Europeneeds to develop technologies towards self-sufficiency in energy and water and keep materials requiredfor consumption flowing [1]. This will insure reduction in virgin resources and treat waste as a valuableinput rather than a burden for welfare of society and the environment.RESYNTEX, the European Union’s Horizon 2020 research and innovation funded program, will producesecondary raw materials from blends and pure components of unwearable textile waste and is expectedto have a strong circular economy focus. The project will develop and demonstrate a strategic design forclosed loop textile recycling throughout the value chain.
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| 7. |
- Kupka, Karel, et al.
(författare)
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Characterizing Business Resilience Using SVM-Based Predictive Modeling
- 2016
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Ingår i: Meeting on Statistics in Business and Industry. - Barcelona, Spain. ; , s. 39-40
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Business resilience has gained prominence, in academia and practice, vis-à-vis the heightened challenges recently faced by organizations, e.g. financial crisis. Developing resilience by thriving or bouncing back from crises yields sound business health in the future.However extant scholarly discussion on predictive modelling of economic resilience is rather limited, while business health studies are mainly limited to bankruptcy failure predictions. These studies mostly utilize financial snapshots (based on only few years data) to construct the predictive models hence are static in nature (Balcaen and Ooghe 2006). Several assumptions underpin these static models, e.g. considering failure as a steady process devoid of organizational history (Appiah et al. 2015, du Jardin and Séverin 2011). Even though, few recent studies (cf. du Jardin and Séverin (2011), Chen et al. (2013) etc.) have designed a “trajectory of corporate collapse” to forecast the changes in firms’ financial health, using various ‘expert systems’ like self-organizing maps (SOM) based upon unsupervised neural network approach, these studies still interpret the findings largely for predicting bankruptcy (a ‘state’) rather than drawing inference on the economic growth or recovery patterns (a ‘trajectory’) of organizations – a key to generate resilience. Neither these studies utilize longitudinal financial data (spanning over many years) to capture the dynamics of corporate history required to build resilience of organizations in reality.In this context, our paper proposes developing a predictive econometric model of business resilience by using ‘expert’ SVM method. The expanded predictor based on financial ratios highlighted by Altman (1968)’s Z-score also takes into consideration the corporate dynamics (first and second derivatives). Historical financial data is gathered from 198 firms representing 26 Dow Jones industrial sectors, and starting from 1960s.Our prediction model achieved comparatively high predictive accuracy of ---- (for a forecasting horizon of ----- years) and is comparable to similar studies. However, the main contribution of the paper is in proposing four archetypical patterns in business health trajectories, derived from the historical hind-sight, defined by tendency-dynamics combinations and is essential to characterize business resilience as follows:Business Health (at T = t+1) = Business Health (T = 0 to t) + Resilience functionThese four typical situations range from the most pessimistic case (tendency = Down, dynamics = Down) to the most promising (Up-Up). The four archetypes can be used to explain four resilience functions, viz. (i): up-up as sustainable resilience, (ii) up-down as short-term resilience, till t = T, (iii) down-up as resilience in near-future, at t = T, and (iv) down-down as lack of resilience.
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| 8. |
- Pal, Rudrajeet, et al.
(författare)
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Ambidexterity drivers of value-creation and appropriation in business models: an explorative study from DuPont
- 2017
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Ingår i: Research Journal of Textile and Apparel. - 1560-6074. ; 21:1, s. 2-26
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Tidskriftsartikel (refereegranskat)abstract
- Purpose – This paper aims to investigate how different trajectories can be detected and classified in business models (BMs) at the level of their underlying product development value-structure (value-creation and appropriation), and what are the drivers. Such BMs are run by multinational firms to accommodate various technologies and innovations; however, this is stressful because of inherent incompatibilities and conflicts.Design/methodology/approach – An explorative study of six product cases from Du Pont’s Textiles Fiber Division (DTFD), namely, nylon yarns, knits and wovens, DTFD blockbusters, Coolmax®, MicroMattique™, filling materials and Supriva™, is conducted.Findings – In value-creation, technology push or market pull yields resultant technology-forward or market-back trajectories. For value appropriation, new growth opportunities or continuous market expectations lead to breakthrough or continuous innovations. Consistent and inconsistent combinations of these trajectories yield four differential drivers: technological breakthrough, market-back technology, continuous technology and continuous market-back. This is supported by relevant supply chain strategies, either focused through joint ventures and licensees for commodities or vertically integrated for specialty products.Research limitations/implications – The paper adds to the analysis of ambidexterity in the value structure of BMs along constituent value-creation and appropriation, thus providing a logical lens to understand various complementarities that exist in terms of opposing technology trajectories and product innovation repertoire.Practical implications – This study contributes to the knowledge of product innovation management in the textile industry, where both large-scale innovation and operational excellence are challenged over the past few decades.Originality/value – The lessons learnt address the fundamental issue of higher value generation through configuration of multiple contrasting value-structure elements.
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| 9. |
- Pal, Rudrajeet, et al.
(författare)
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Business health characterization: A hybrid regression and support vector machine analysis
- 2016
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Ingår i: Expert Systems with Applications. - : Elsevier BV. - 0957-4174. ; 49, s. 48-59
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Tidskriftsartikel (refereegranskat)abstract
- Business health prediction is critical and challenging in today's volatile environment, thus demand going beyond classical business failure studies underpinned by rigidities, like paired sampling, a-priori predictors, rigid binary categorization, amongst others.In response, our paper proposes an investor-facing dynamic model for characterizing business health by using a mixed set of techniques, combining both classical and “expert system” methods. Data for constructing the model was obtained from 198 multinational manufacturing and service firms spread over 26 industrial sectors, through Wharton database.The novel 4-stage methodology developed combines a powerful stagewise regression for dynamic predictor selection, a linear regression for modelling expert ratings of firms’ stock value, an SVM model developed from unmatched sample of firms, and finally an SVM-probability model for continuous classification of business health. This hybrid methodology reports comparably higher classification and prediction accuracies (over 0.96 and ∼90%, respectively) and predictor extraction rate (∼96%). It can also objectively identify and constitute new unsought variables to explain and predict behaviour of business subjects.Among other results, such a volatile model build upon a stable methodology can influence business practitioners in a number of ways to monitor and improve financial health. Future research can concentrate on adding a time-variable to the financial model along with more sector-specificity.
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| 10. |
- Pal, Rudrajeet, et al.
(författare)
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From classical business failure prediction models to business financial models for resilience : using advanced statistical methodologies
- 2015
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Konferensbidrag (refereegranskat)abstract
- Over the last 35 years business failure prediction using various methods like univariate analysis, multi-variate analysis, credit risk models etc. has become a major research domain within corporate finance (Balcaen and Ooghe 2006). These mathematical models are increasingly accepted by financial institutions, governments and the European Union in the Basel Accords (Basel II/III). However, most classic statistical failure prediction models are developed without comprehensive understanding of the nature of company failure with often arbitrarily variables chosen in an ad-hoc manner (Beaver 1967b, Cybinski 2001). In this context, the paper uses advanced statistical methodology to propose a robust business financial modeling technique. Data on 18 key financial parameters were collected for 198 US-based public companies along with their expert credit rating for 2012-13. Firstly, a correlation study was performed between Altman scores and widely accepted expert rating based on stock exchange activities. Secondly, “stage-wise” regression was conducted to select the statistically most significant candidate ratios (from 153 to 9) (Hastie et al. 2007a). Thirdly, linear regression model was employed to model the credit rating and also to reduce the candidate variables (from 9 predictor ratios to five those were statistically significant). Fourth, the significant variables were used to construct the decision plane for the linear discriminant model using support vector machine classifier (SVM-C) estimation procedure (Scholkopf et al. 1995, Vapnik 1998). Binary response variable was obtained by dividing the ratings into two groups: high rating (or “good companies”) and low rating (or “not so good companies”) by choosing an arbitrary threshold rating value. Finally a logistic regression model helped to define the probability of having high rating (i.e. greater than 5) for a given company. Findings were manifold. The correlation between the Z-score and rating was poor (0.0223 and 0.0133 respectively for manufacturing and service companies). The linear regression models, on the other hand, showed high correlation coefficient (0.64 and 0.71 respectively) between predicted and actual expert ratings. With a few exceptions, in the heavy industry sectors, data was homogeneous (found using predicted residual method). The equation of the new discriminating hyper plane created by the SVM classification model (termed as Investor Inclination Index - I3 model) was proposed which means that expert ratings can be more significantly correlated to a set of candidate financial ratios predicting it. These are: (i) Cost of Goods Sold/Total Operating Expenses, (ii) Earnings Before Interest and Taxes/Total Liabilities, (iii) Earnings Before Interest/Total Revenue, (iv) Retained Earnings/Total Revenue, and (v) Working Capital/Research and Development Expense. The paper contributes by updating the original Altman discriminant model by using a data-driven predictor selection strategy to create a general methodology for building financial models providing economic meaningfulness to the credit rating used for assessing company’s performance and health. A wider use of validated financial models will encourage corporate businesses and even SMEs to evaluate themselves internally thus allowing them to identify possible threats and improve credit rating. Future research aims to provide explicit economic meaningfulness to the individual predictor ratios so that companies can create a strategic resource model (SRM) by interpreting the I3 model to determine how to create a decision support aid for the company’s business management. Also authors aim to extend the contribution by developing a tendency-dynamic status to the financial predictor for incorporating a time-series behavior for pattern recognition. This will provide economic meaningfulness to the financial models; predict financial risk and means to be resilient.
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