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Ecosystems’ digitally enabled networks that enhance corporate value propositions by linking corporate units, suppliers, distributors, partners, customers and other stakeholders -- have become the engine that drives performance and strategic impact across economies. Article examines which ecosystem strategies are appropriate for firms in various situations.

A new IBM Institute for Business Value (IBV) survey of 700 executives involved in decision-making about their organizations’ ecosystem growth and partnering reveals that the companies most focused on ecosystem engagement consistently generate higher growth and more business value.

Analysis of the executive responses identified four distinct strategic approaches for ecosystem activity – Accelerate, Expand, Ignite and Reposition.

Success is likely only if firms pursue the right ecosystem strategy for their situation, with the right business partners, executed the right way.

Ecosystems can enhance the value of products or services through both competition and cooperation with partners and rivals. For enterprises battling dislocation and disruption, ecosystems promote agility and resilience and can identify new revenue opportunities. As such, ecosystems have been the essential vehicle for growth and expansion for many corporations.

Outlines why India is poised to be a key partner in the global ecosystem economy

Researches the advantage India has and the steps it is taking to make itself a leaders in ecosystem businesses.

54 percent of Indian executives expect ecosystems to replace traditional value chains with new value models. and 92 percent expect to change primary organizational activities due to the emergence of ecosystems.

To maximize and capture benefits from ecosystems, business, educational and government leaders can pursue three key steps to participate in rapidly emerging Indian business ecosystems.

This study puts together both the corporate and governmental actions that promote the right conditions for ecosystem entrepreneurship so that potential partners have a unique view of the opportunities to participate in this rapidly changing economy.

To better understand the challenges and opportunities facing China, the IBM Institute for Business Value in cooperation with Oxford Economics surveyed 1,150 executives from across China. Survey respondents represented a variety of industries and included executives from Chinese corporations, start-up enterprises, the government sector and educational institutions.

This report shares the executives’ vision for the Chinese economy, and proposes actions to help spark growth and positive change.

The Chinese executives surveyed see the current economic environment in China as encompassing five main challenges – immature services sector, declining domestic consumption growth, lending decisions creating over investment in some sectors, declining export growth and environmental issues impacting economic development.

The article identifies the six most important ways to accelerate China’s growth according to the executives:

Despite challenges, Chinese executives are optimistic about the country’s economic growth prospects. In fact, 93 percent of executives believe China will maintain stable to high growth of more than 5 percent over the next five years. And almost a quarter of them believe China will be able to return to its recent very high growth rates in excess of 8 percent.

The objective of this paper is to propose a methodology based on random demand inventory models and dependence structures for a set of raw materials, referred to as “components”, used by food services that produce food rations referred to as “menus”.

The contribution margins of food services that produce menus are optimised using random dependent demand inventory models. The statistical dependence between the demand for components and/or menus is incorporated into the model through the multivariate Gaussian (or normal) distribution. The contribution margins are optimised by using probabilistic inventory models for each component and stochastic programming with a differential evolution algorithm.

When compared to the non-optimised system previously used by the company, the (average) expected contribution margin increases by 18.32 per cent when using a continuous review inventory model for groceries and uniperiodic models for perishable components (optimised system).

The multivariate modeling can be improved by using (a) other non-Gaussian (marginal) univariate probability distributions, by means of the copula method that considers more complex statistical dependence structures; (b) time-dependence, through autoregressive time-series structures and moving average; (c) random modelling of lead-time; and (d) demands for components with values equal to zero using zero-inflated or adjusted probability distribution.

Professional management of the supply chain allows the users to register data concerning component identification, demand, and stock levels to subsequently be used with the proposed methodology, which must be implemented computationally.

The proposed multivariate methodology allows it to describe demand dependence structures through inventory models applicable to components used to produce menus in food services.

Este trabajo propone una metodología basada en modelos de inventarios con demanda aleatoria y estructura de dependencia para un conjunto de materias primas, denominadas “componentes”, usadas por servicios de alimentación que producen raciones alimenticias denominadas “menús”.

Los margen de contribución de servicios de alimentación que producen menús son optimizados empleando modelos de inventarios con demandas aleatorias dependientes. La dependencia estadística entre demandas de componentes y/o menús es incorporada en el modelado mediante la distribución gaussiana (o normal) multivariada. La optimización de los márgenes de contribución se logra usando modelos de inventarios probabilísticos para cada componente y programación estocástica mediante el algoritmo de evolución diferencial.

El margen de contribución esperado (promedio) aumenta en un 18,32% usando modelos de inventario de revisión continua para abarrotes y modelos uniperiódicos para componentes perecederos (sistema optimizado), en relación al sistema no optimizado usado anteriormente por la compañía.

La metodología multivariada propuesta permite describir estructuras de dependencia de la demanda mediante modelos de inventario aplicables a componentes usados para producir menús en servicios de alimentación.

Una administración profesional de la gestión de la cadena de suministros permite registrar datos de la identificación del componente, su demanda y sus niveles de stock para ser usados posteriormente con la metodología propuesta, la que debe estar implementada computacionalmente.

El modelado multivariado puede ser mejorado (a) utilizando distribuciones probabilísticas univariadas (marginales) distintas a la gaussiana, mediante métodos de cópulas que recojan estructuras de dependencia estadística más complejas; (b) considerando demandas de componentes con valores iguales a cero, mediante distribuciones probabilísticas infladas en cero; (c) usando dependencia temporal, mediante estructuras de series de tiempo autorregresivas y de media móvil, y (d) modelando el lead-time en forma aleatoria.