دانلود مقاله ISI انگلیسی شماره 7767
عنوان فارسی مقاله

توسعه سناریو برای صنعت بیمه بهداشت و درمان در حال تکامل در مناطق روستایی هند : ورودی برای نوآوری در مدل کسب و کار

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
7767 2012 12 صفحه PDF سفارش دهید 9650 کلمه
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عنوان انگلیسی
Scenario development for an evolving health insurance industry in rural India: INPUT for business model innovation
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Technological Forecasting and Social Change, Volume 79, Issue 4, May 2012, Pages 688–699

کلمات کلیدی
توسعه سناریو - تجزیه و تحلیل استراتژیک - دلفی - روستایی هند - بیمه بهداشت و درمان - کارشناس داوری - نوآوری در مدل کسب و کار
پیش نمایش مقاله
پیش نمایش مقاله توسعه سناریو برای صنعت بیمه بهداشت و درمان در حال تکامل در مناطق روستایی هند : ورودی برای نوآوری در مدل کسب و کار

چکیده انگلیسی

The article discusses the use of Delphi-based scenarios for the development of business model innovations in emerging markets. Motivated by insights from information processing and institutional theory we present a scenario development process combining a PEST (political, economic, socio-cultural, and technological) and a stakeholder approach. We exemplify its use for the evolving health insurance market in rural India and present how our approach can be used to study possible future developments relevant for business model innovations. Key insights are that NGOs might play a crucial role along with the regulatory support of the Government of India and significant advances in mobile payment technologies.

مقدمه انگلیسی

Innovations are a major driver for economic growth and have successfully contributed to societal and corporate wealth in developed countries in the past [1] and [2]. In order to stay competitive societies and companies alike have to innovate on a regular basis and introduce new products and services successfully [3] and [4]. Today, innovations are especially gaining importance for companies and societies in emerging markets as they are now facing global competition after a long period of only domestic competition if at all [5] and need to tackle multifaceted challenges of economic, ecological and social change. A new and promising playground for future innovations exists therefore in emerging markets such as India. Up to 75% of the world's economic growth is expected to be generated in these markets in the short- to mid-term future [6]. Attracted from the enormous growth potential in those countries, multinational as well as domestic corporations put considerable efforts into the understanding of how to optimally benefit from the developments in these markets. The literature reveals that companies simply transferring their business models and operations of established markets to emerging markets are often not successful. Anecdotal and empirical evidence rather suggests that substantial adaptations to successful business models need to be applied in order to successfully operate in emerging markets [7], [8] and [9]. In the case of India, various adaptations to business models and operations are normally necessary to serve both the urban and rural areas as these markets nowadays often substantially differentiate in their specific product and service requirements. Business models appropriate for the specific conditions of rural areas in emerging countries should also aim at levering the strengths of this special market rather than focussing on overcoming their weaknesses from a developed market perspective [9]. An essential requirement for successful business model innovation in emerging markets seems the information gathering and processing of the current industry environment from a political, economic, social or technological perspective and the adjacent analysis of how these dimensions may evolve over time. The challenge of collecting and processing information regarding the environment of an industry becomes even more complex when the focus is set on emerging markets such as India. This also results from the fact that emerging markets are characterised by dynamic institutional change, a lack of transparency of decision-making in many governmental and other relevant institutions, and the opaqueness of regulations [10]. Dynamic institutions and frequent changes in governmental regulations such as tax laws or FDI limits, business practices, competitive behaviour, or market growth boost the level of uncertainty for decision makers. Hence, it seems beneficial to think about alternative futures as emerging markets do often not develop in a linear, predictable way [10] and [11]. In such an environment, it is increasingly difficult for managers to process information and make effective decisions. It becomes even more difficult when the familiarity with a specific market environment is rather low due to geographical distance or missing cultural understanding. This phenomenon can frequently be observed in multinational companies operating in India being headquartered in Europe or the US. In such situations, the likelihood to accidentally neglect relevant factors, filter out important information, or draw misleading clues is high [12]. It becomes more difficult for senior executives to obtain, analyse, and verify information about the relevant environment for their industry [13]. The objective of our paper is to present how future-oriented information can be generated in order to successfully develop and adapt business models for emerging markets especially in the case of evolving industries where fully developed business models do not exist yet. In the remainder of this paper we discuss how Delphi-based scenarios can be developed and used to analyse how an industry in an emerging market may evolve in the future and to understand which elements of business models might be required to get substantially adapted, radically changed or newly created in order to be successful. First, we discuss the theoretical background for future-oriented industry analyses and explain our approach based on information processing and institutional theory. We then draw on the results of a Delphi study in which we surveyed more than 35 local experts to present how scenarios for the health insurance industry in rural India might look like by 2020 and how a business model might accordingly be developed or adapted.

نتیجه گیری انگلیسی

Emerging markets such as India are considered to provide remarkable growth opportunities in diverse industries in the future. An increasing number of multinational companies have entered the Indian market aiming to benefit from the current and predicted two-digit growth rates in many industries. Companies which simply transfer their existing business models from developed and mature to emerging markets are most often not successful. Substantial adaptations and business model innovations are required to successfully operate in emerging markets [7], [8] and [9]. In order to identify these required business model innovations and adaptations effectively, it becomes necessary to systematically analyse the future business environment of an industry in an emerging market considering especially political, economic, socio-cultural, and technological aspects. Due to the fact that emerging markets are characterised by high levels of uncertainty and instability [10], it becomes more difficult for senior executives to obtain, analyse, and verify information about the relevant context within they have to make their decisions [13]. Thus, their information processing requirements become more complex. According to the literature, future-oriented information analysis becomes increasingly important in such situations. Different approaches have been developed in the literature to demonstrate how to systematically analyse possible futures and to prepare organisations for challenges to come. However, there is a gap in the literature addressing the question how future-oriented knowledge can be generated and how they can be used to develop appropriate business model innovations for emerging markets. In this paper, we presented how Delphi-based scenarios can be developed in a structured way to investigate how, as an example, the health insurance industry in rural India could develop until 2020. Thereby, we developed two different types of projections. Whilst outcome projections were structured around political, economic, socio-cultural, and technological (PEST) dimensions, we also developed stakeholder-based enabler projections which analysed relevant activities of stakeholders such as consumers, competitors, suppliers, government, and the society influencing the industry's future. Thus, our results can be used for decision makers in the health insurance industry to develop business model innovations and resource investment strategies which are robust and integrate the flexibility to adapt to different scenarios. By illustrating how different stakeholder groups influence possible future outcomes, decision makers can prioritise their attention for different stakeholder groups. If important stakeholders are observed carefully and their actions are interpreted correctly, decision makers can increase the chance to draw correct conclusion about which scenarios might occur in the future and which business model adaptations and innovations will be required within these scenarios. In the case of the evolving health insurance industry in rural India we observed first of all that many experts were very much focusing on their specific area of expertise only when justifying their judgments. Arguments provided by other industry stakeholder groups were often neglected. However, when looking at the results from a neutral researcher perspective it becomes obvious that a focus on specific elements of a health insurance system in rural India only is not sufficient. The interdependencies between different stakeholders such as government, NGOs, mobile payment solution providers and insurance companies are extremely high. For example, the Government of India has a high interest that health insurance is widely accepted and accessible to low-income groups in rural India. However, private health insurance in such areas only represents a real value if there is sufficient medical support available for all kinds of insured treatments. Such a medical support system can only be provided at acceptable costs when the existing government-owned infrastructure such as hospitals and basic medical equipment can be used by every interested medical service provider. Such a system would be comparable to a railways system where the government owns the tracks and any private company can use them with their trains in exchange for a reasonable network user fee. Similar, transaction costs regarding deal making and regular payments need to be reduced drastically to make health insurance products both interesting for low-income groups and economically viable for health insurance providers. Such a drastic reduction of transaction costs seems today only possible through the provision of cost-efficient and effective mobile payment or similar solutions on the one hand and the use of existing distribution systems such as NGOs on the other hand. For senior executives in the Indian health insurance business is actually not priority to focus on the development of different insurance products. They are rather required to establish collaborations with medical and mobile payment service providers as well as NGOs to jointly convince the government to provide the necessary infrastructure to improve medical services in rural India significantly. Another insight for senior executives is that the establishment of efficient sales channels through NGOs is a key priority even if only a few insurance policies are currently sold. As soon as medical support improves and especially suitable mobile payment solutions are available the direct access to potential customers through the local NGOs will be key to fast gain substantial market shares.

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