A market based approach for resolving resource constrained task allocation problems in a software development process

We consider software development as an economic activity, where goods and services can be modeled as a resource constrained task allocation problem. This paper introduces a market based mechanism to overcome task allocation issues in a software development process. It proposes a mechanism with a prescribed set of rules, where valuation is based on the behaviors of stakeholders such as biding for a task. A bid process ensures that a stakeholder, who values the resource most, will have it allocated for a limited number of times. To observe the bidders behaviors, we initiate an approach incorporated with a process simulation model. Our preliminary results support the idea that our model is useful for optimizing the value based task allocations, creating a market value for the project assets, and for achieving proper allocation of project resources specifically on large scale software projects

Asset specificity and behavioral uncertainty as moderators of the sales growth: Employment growth relationship in emerging ventures

Sales growth and employment growth are the two most widely used growth indicators for new ventures; yet, sales growth and employment growth are not interchangeable measures of new venture growth. Rather, they are related, but somewhat independent constructs that respond differently to a variety of criteria. Most of the literature treats this as a methodological technicality. However, sales growth with or without accompanying employment growth has very different implications for managers and policy makers. A better understanding of what drives these different growth metrics has the potential to lead to better decision making. To improve that understanding we apply transaction cost economics reasoning to predict when sales growth will be or will not be accompanied by employment growth. Our results indicate that our predictions are borne out consistently in resource-constrained contexts but not in resource-munificent contexts.</p

In Search of the Market: Lessons from Analyzing Agricultural Transition in Central and Eastern Europe

Studies of the transition process remind us of Stiglitz's comparison between pathology and the economic analysis of institutions (1989): asking what went wrong and what did not is the essence of understanding the functioning of social systems. Thus, carefully conducted empirical studies of the transition process itself may yield elucidative results applicable not only to theory but also to institutional policy changes in transition. This paper presents the key findings of KATO, a comprehensive research project focussing on the transition process of agriculture in Central and Eastern Europe. From 1997 to 2000, the project empirically examined processes of liberalization and market development, privatization and property rights changes, as well as restructuring and path dependencies in three Central and Eastern Europe countries: Poland, the Czech Republic and Bulgaria. Conclusions on three analytical levels are drawn: (1) the empirical design for analyzing rapidly changing and evolving institutions in transition economies, (2) the suitability of different theoretical approaches for understanding transition, and (3) policy recommendations targeting better governance and an improved institutional framework.Agricultural and Food Policy,

Beyond categorization: new directions for theory development about entrepreneurial internationalization

Categorizations emphasizing the earliness of internationalization have long been a cornerstone of international entrepreneurship research. Here we contend that the prominence of categories has not been commensurate with theory development associated with them. We draw on categorization theory to explain why earliness-based categories are persistent, and argue that a greater focus on notions related to opportunity can open new avenues of research about the entrepreneurial internationalization of business. We propose and discuss three directions for opportunity-based research on entrepreneurial internationalization, involving context, dynamics and variety

Managing Process Variants in the Process Life Cycle

When designing process-aware information systems, often variants of the same process have to be specified. Each variant then constitutes an adjustment of a particular process to specific requirements building the process context. Current Business Process Management (BPM) tools do not adequately support the management of process variants. Usually, the variants have to be kept in separate process models. This leads to huge modeling and maintenance efforts. In particular, more fundamental process changes (e.g., changes of legal regulations) often require the adjustment of all process variants derived from the same process; i.e., the variants have to be adapted separately to meet the new requirements. This redundancy in modeling and adapting process variants is both time consuming and error-prone. This paper presents the Provop approach, which provides a more flexible solution for managing process variants in the process life cycle. In particular, process variants can be configured out of a basic process following an operational approach; i.e., a specific variant is derived from the basic process by applying a set of well-defined change operations to it. Provop provides full process life cycle support and allows for flexible process configuration resulting in a maintainable collection of process variants

Supporting knowledge exchange isn't easy: lessons learnt from a case study

A knowledge management system is introduced in a large insurance company. It is meant to become a virtual knowledge network for a group of insurance professionals. Despite the fact that the introduction was met with enthusiasm and user participation in the design was ensured, the system did not live up to the expectations. In this paper we investigate this failure by uncovering and analyzing the requirements engineering processes underlying the system's\ud conception, design and introduction. The demise of the system can be attributed to a lack of attention for the use context of the end users and a tendency in the development process to focus mostly on the technical solution instead of problem analysis

A formal verification framework and associated tools for enterprise modeling : application to UEML

The aim of this paper is to propose and apply a verification and validation approach to Enterprise Modeling that enables the user to improve the relevance and correctness, the suitability and coherence of a model by using properties specification and formal proof of properties

Moving from Data-Constrained to Data-Enabled Research: Experiences and Challenges in Collecting, Validating and Analyzing Large-Scale e-Commerce Data

Widespread e-commerce activity on the Internet has led to new opportunities to collect vast amounts of micro-level market and nonmarket data. In this paper we share our experiences in collecting, validating, storing and analyzing large Internet-based data sets in the area of online auctions, music file sharing and online retailer pricing. We demonstrate how such data can advance knowledge by facilitating sharper and more extensive tests of existing theories and by offering observational underpinnings for the development of new theories. Just as experimental economics pushed the frontiers of economic thought by enabling the testing of numerous theories of economic behavior in the environment of a controlled laboratory, we believe that observing, often over extended periods of time, real-world agents participating in market and nonmarket activity on the Internet can lead us to develop and test a variety of new theories. Internet data gathering is not controlled experimentation. We cannot randomly assign participants to treatments or determine event orderings. Internet data gathering does offer potentially large data sets with repeated observation of individual choices and action. In addition, the automated data collection holds promise for greatly reduced cost per observation. Our methods rely on technological advances in automated data collection agents. Significant challenges remain in developing appropriate sampling techniques integrating data from heterogeneous sources in a variety of formats, constructing generalizable processes and understanding legal constraints. Despite these challenges, the early evidence from those who have harvested and analyzed large amounts of e-commerce data points toward a significant leap in our ability to understand the functioning of electronic commerce.Comment: Published at http://dx.doi.org/10.1214/088342306000000231 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org