基于ERP系统的建筑企业信息化建设风险评价研究

从建筑企业管理者的角度出发,针对建筑企业实施ERP的盲目性,在问卷结果分析和建筑企业内部风险因素分析的基础上,建立了实施ERP阶段的内部风险评价指标体系.引入了技术创新项目风险评价的典型模型,考虑ERP项目实施的失败概率及其预期损失,结合专家调查法,提出集值统计一专家调查法的多因素风险评价模型,并给出了风险标准参考值,为实现企业不同需求的风险自评价提供了简便易行的操作方法和可靠科学的后期决策依据,以期促进建筑企业信息化建设.     

Sectoral Heterogeneity in New Service Development: An Exploratory Study of Service Types and Success Factors

The service industry is of fundamental relevance for the economies of industrialized countries, as the service industry produces the highest growth in the gross domestic product. In this regard, new service development (NSD) represents a critical resource for competitive survival and a decisive factor of growth in the service industry. However, service firms across many industries are increasingly faced with the challenge of determining how best to manage their development of new service offerings. Although researchers have shown growing interest in NSD issues, this area is still underutilized. Furthermore, although the heterogeneity of the service industry has been emphasized for years, the current body of research on NSD mainly focuses on specific service environments, providing data that are often not comparable across different service sectors. Additionally, there is no study to date that comprehensively examines innovation activities and the relevance of service innovations’ success factors within different service industries. The aim of this exploratory study is to establish a more balanced picture of the nature of innovation activities in terms of NSD characteristics and success factors in the heterogeneous service industry. From this perspective, this paper begins with an examination of the factors that contribute to the success of NSD. Based on a meta‐analysis of new service success factor studies, 17 different success determinants are classified and aggregated to service‐related success determinants. Subsequently, a cluster analysis of 1016 service companies is used to identify different service innovation types. For the service sector, four service innovation types are determined: efficient developers, innovative developers, interactive adopters, and standardized adopters. Furthermore, based on interviews with service innovation managers, the previously identified success factors are examined for each innovation type using a standardized survey. Finally, based on the results of this exploratory study, the paper concludes with recommendations for NSD management and research propositions for each service innovation type. These propositions support innovation managers to successfully manage service innovations for the innovation type they are operating in.     

Does the level of experience have an effect on CRM programs? Exploratory research findings

A growing body of academic and practitioner literature has highlighted the differences in definitions and approaches to customer relationship management (CRM), suggested frameworks for successful CRM implementation, and provided evidences of CRM success and failure. Such accumulating wisdom might be expected to imbue practice with knowledge of what works better in CRM and to entail, therefore, an improving experience of CRM over time. To date, however, the effect of experience on CRM implementation has not been discussed in literature. This paper studies CRM from the organisational learning perspective. It provides evidence from empirical research conducted among users (firms), consultants, and suppliers (software vendors) about the effect of experience on CRM. The exploratory research findings of this study draw attention to the extent to which firms deploying CRM are sensitive and responsive to what they might learn from their implementation efforts and establish a platform for future research. The paper suggests the need for the two processes of CRM and organisational learning to move in tandem to be mutually beneficial.     

Will It Spread or Not? The Effects of Social Influences and Network Topology on Innovation Diffusion

Innovation diffusion theory suggests that consumers differ concerning the number of contacts they have and the degree and the direction to which social influences determine their choice to adopt. To test the impacts of these factors on innovation diffusion, in particular the occurrence of hits and flops, a new agent‐based model for innovation diffusion is introduced. This model departs from existing percolation models by using more realistic agents (both individual preferences and social influence) and more realistic networks (scale free with cost constraints). Furthermore, it allows consumers to weight the links they have, and it allows links to be directional. In this way this agent‐based model tests the effect of VIPs who can have a relatively large impact on many consumers. Results indicate that markets with high social influence are more uncertain concerning the final success of the innovation and that it is more difficult for the innovation to take off. As consumers affect each other to adopt or not at the beginning of the diffusion, the new product has more difficulties to reach the critical mass that is necessary for the product to take off. In addition, results of the simulation experiments show under which conditions highly connected agents (VIPs) determine the final diffusion of the innovation. Although hubs are present in almost any network of consumers, their roles and their effects in different markets can be very different. Using a scale‐free network with a cut‐off parameter for the maximum number of connections a hub can have, the simulation results show that when hubs have limits to the maximum number of connections the innovation diffusion is severely hampered, and it becomes much more uncertain. However, it is found that the effect of VIPs on the diffusion curve is often overestimated. In fact when the influence of VIPs on the decision making of the consumers is strengthened compared with the influence of normal friends, the diffusion of the innovation is not substantially facilitated. It can be concluded that the importance of VIPs resides in their capacity to inform many consumers and not in a stronger persuasive power.     

Developing customised CRM projects: The role of industry norms,organisational context and customer expectations on CRM implementation

This research paper investigates the influence of industry, organisational, and customer context on customer relationship management (CRM) projects. Organisations go through four phases in their CRM projects (assessment, design, implementation, and evaluation), yet the impact of industry norms, organisational contexts, and customer expectations on each phase are rarely examined. A longitudinal case study approach with six cases was used to investigate the potential impact of contextual factors on CRM projects. The cases covered a range of industries, organisational structures, and customer types. We found that current industry conditions and customer expectations influence the reasons for undertaking CRM and the assessment stage of the project. The organisational context has a noticeable impact on the design and implementation project stages. At the evaluation level, customer responses combined with organisational expectations affect the perceived success of the projects. By understanding the impact of context, customised CRM projects can be developed.     

Organisational, technical and data quality factors in CRM adoption — SMEs perspective

Like large organisations, many Small and Medium-sized Enterprises (SMEs) have implemented Customer Relationship Management (CRM), so that they can compete effectively in today's highly changeable economic and market climate. However, studies indicate that there are mixed results as to how successful SMEs have been in adopting CRM solutions. It is also reported in the literature that CRM implementation is influenced by issues that relate to organisational, technical and data quality factors. To this end, there is limited research conducted in this area which mainly focuses on including these dimension in the evaluation of factors that influence CRM adoption in the SME sector. In seeking to address this issue, this research uses an investigative study aimed at identifying the organisational, technical and data quality related factors influencing CRM adoption by SMEs. This will enhance the quality of the evaluation process, and help support SME decision makers in exploring the implications surrounding CRM adoption. The findings of this study confirm that factors affecting the adoption of CRM in SMEs are largely similar to the factors affecting CRM adoption in previously studied other types of organisations.     

A relationship-management assessment tool: Questioning, identifying, and prioritizing critical aspects of customer relationships

With customer-relationship management (CRM) no longer a buzzword among trendsetters, organizations in all types of industries initially rushed to embrace it. Although a seductively attractive concept, the implementation of CRM proved difficult, however, and organizations are struggling with realizing their vision of a CRM organization. To help managers assessing the stage of relationships between their organization and the organization's business customers we consider the automotive industry. Based upon our case organization and its relationships with numerous business customers we develop a practical tool to question, identify, and prioritize critical aspects of customer-relationship management. First, we identify key areas in CRM. Secondly, we investigate how the chosen case organization has managed each of these key CRM areas over a broad range of business-customer relationships. Thirdly, we acknowledge that many organizations simultaneously have different types (transaction-relationship continuum) of business customers. We finish the article with a discussion of the study's limitations, and suggest avenues for future research.     

Antecedents and consequences of CRM technology acceptance in the sales force

Two conceptual approaches [Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319-340; DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3 (1), 60-95] are unified into a conceptual model that offers a comprehensive explanation of CRM acceptance antecedents and consequences in a sales force setting. Based upon responses from 240 salespersons that utilize a CRM system, the model is tested and explanations are offered for the system's acceptance. Specifically, the most prevailing influence on CRM acceptance comes from CRM perceived usefulness, followed by the setting of accurate expectations regarding system usage, the salesperson innovativeness towards new technological tools, the CRM perceived ease-of-use, and the supervisor encouragement and support. Surprisingly, the model does not adequately explicate salesperson performance. Sales managers are presented with a discussion and implications of the findings.     

Identifying industrial new product success: Project NewProd

What is the key to success in industrial product innovation? This question is frequently posed, and many authors and managers have speculated as to which critical factors or variables decide the fate of new industrial products. What is missing in the debate is evidence based on actual new product successes and failures. Project NewProd is an investigation that was designed to fill this void. In this article we report the results of a study into a large number of successful and unsuccessful new products, project NewProd, whose goal was to identify the determinants of commercial success in industrial product innovation.     

Success Factors in Product Innovation: A Selective Review of the Literature

In today's increasingly competitive climate, more and more managers are having to update themselves on the range of factors that determine product innovation success. Such successes can be measured at the project (product) level or at the program level. Axel Johne and Patricia Snelson have prepared a review of factors associated with achieving success in a high proportion of recently developed new products. The authors address practical questions, such as the following: To what extent can product innovation be planned? Should development tasks be scheduled sequentially or in parallel? What is the proper degree of formality in effective new product decision making? What are the optimal organizational arrangements? The article concentrates on recent writings, drawing chiefly from journal articles published after 1980, including a large number from the Journal of Product Innovation Management. Factors contributing to success are ordered according to the now well-known McKinsey 7 Ss framework popularized by Peters and Waterman in their book In Search of Excellence. Detailed development tasks are considered according to the schema advanced by Crawford in his book New Products Management.     

A systematic small group approach to creativity and innovation: A case study

The paper reports a longitudinal study of the result of applying systematic creative problem-solving techniques in a particular multinational firm. The first section of the paper describes the way the system was applied to the five stages of an innovation from conception to implementation. Fifteen different techniques were used, the choice varying with the stage. The paper then describes three examples of actual innovations (disguised), stage by stage, giving a judgment of the value of the techniques used, the frequency of success or failure of all the sessions undertaken, the relative success of the techniques used, and the usage of the techniques by stage of innovation.
Two further points are made; firstly, creative thinking is needed and manifested at all stages of a project and not just in the early stages; secondly, although Synectics was shown to be rather effective it gradually lost ground to a less successful technique because the managers concerned did not like its seeming inconsequentiality and abandonment of logic.     

From Experience: Linking Product Innovation to Business Growth

Industry pundits often take managers to task for their supposedly myopic approach to planning and decision making. These sweeping generalizations gloss over the complex challenges confronting the managers who must ensure that their firms enjoy ongoing revenue growth opportunities. In place of pat answers, those managers require analysis and planning tools that offer clearer insights into the effects their decisions have on their firms' continued business success. As Marv Patterson points out, however, determining the effects of product innovation decisions poses a particular challenge for management, because the consequences of those decisions typically do not become evident until long after the decisions have been made. Presenting a conceptual model that links product innovation activities to revenue growth, he identifies three drivers of revenue growth, and explains how these growth drivers are linked by a set of mathematical relationships that can be presented in the form of an enterprise-specific growth table. He applies the model to three types of enterprises, and he discusses the key implications that the model holds for the business leaders who must keep shareholders satisfied. He depicts the relationship between a company and its customers as a closed-loop system in which the company converts labor, parts, and material into products, which it delivers to customers. The company invests a portion of the resulting revenue stream in the resources that generate new products. By effectively and continually applying a sufficiently large investment in this innovation engine, the company creates an ongoing stream of new products. The revenues from these new products more than offset the drop in revenues from products that are approaching obsolescence. He identifies three factors that drive revenue growth from these investments in the innovation engine: the fraction of revenues invested in product innovation, new product revenue gain, and the behavior of revenue over time for a particular business. Using a graph called a product vintage chart, he demonstrates that for a large company, the revenue contributions of a particular new-product year (or vintage) fall into a regular pattern over time, which enables a company to determine mathematical relationships for revenue growth as a function of R&D investment and new product revenue growth. In this way, senior managers can gain clearer understanding of the interplay between product innovation, R&D investment, revenue growth, and profitability over time.     

Passion for Work,Nonwork‐Related Excitement,and Innovation Managers’ Decision to Exploit New Product Opportunities

This article investigates the role of affect in innovation managers’ decision to exploit new product opportunities—a decision central to the innovation process. The model proposes that different types of passion can trigger managers’ exploitation decisions but that this effect is contingent on experiencing excitement from events outside their work environment. A field experiment with 90 owner–managers of young firms located in an innovation context (business incubators) shows that passion for work and nonwork‐related excitement levels interdependently impact innovation managers’ decision to exploit new product opportunities. Specifically, harmonious passion has a general positive effect on managers’ propensity to exploit. In contrast, the effect of obsessive passion is more complex and contingent on the additional excitement managers experience such that the positive relationship between obsessive passion and the decision to exploit is more positive with higher levels of excitement. These findings extend the product innovation management literature by acknowledging that decision‐makers’ affective experiences influence innovation decisions and provide a first step toward understanding the role of affect and passion in the product innovation context. Second, the finding that obsessive passion and nonwork‐related excitement interact in explaining opportunity exploitation decisions highlights the need to incorporate contingency relationships in models of innovation decision‐making. Third, in drawing on a field experiment and the experimental manipulation of managerial affect during the decision‐making task, this article answers a recent call in the project management literature to pursue less common methodological approaches and develop “broader theoretical schema” in order to enhance our understanding of innovation management. Finally, this study also has implications for practitioners because it can help innovation managers understand their own decision policies. To the extent that innovation managers are able to regulate their affective experiences, this improved understanding might prevent them from premature and faulty decision‐making.     

Factors Affecting New Product Success: Cross-Country Comparisons

Although considerable effort has been devoted to identifying the factors that contribute to new product success and failure, plenty of work remains to be done in this area. For example, many studies of this subject focus on companies in specific parts of the world (in particular, North America, Europe, and Japan). It remains to be seen whether the findings from these studies apply to the new product development (NPD) efforts of companies in other regions, let alone on a global basis. Sanjay Mishra, Dongwook Kim, and Dae Hoon Lee address this issue in a study of the factors that contribute to the success or failure of NPD efforts in South Korean firms. To explore the question of whether a global set of success factors can be identified, they compare their findings with those of similar studies conducted in Canada and China. Classifying these countries in terms of stages of economic development (with China and Canada at opposite extremes and Korea in the middle), they expect to find the greatest dissimilarities in their comparisons of China and Canada. Marketing managers from 144 Korean firms provided in formation about 288 successful and unsuccessful products. Their responses indicate that the factors most closely related to new product outcomes in Korea are market intelligence, product-firm compatibility, the nature of the new product idea (for example, whether the product idea was market derived, whether the product specifications were clearly defined by the marketplace), launch effort, and general characteristics of the new product venture (such as the product's innovativeness to the market and its technical complexity). Several of these factors were emphasized in studies of Canadian and Chinese NPD success, though respondents to those studies also highlighted the importance of the product offering and proficiency of formal NPD activities. Contrary to expectations, China and Canada show the greatest similarity among the three countries studied, in terms of the relative importance of the various NPD success factors. On the other hand, China and Korea are more similar in terms of the effects of the variables studied. In other words, if a variable is related to new product failure in Korea, that variable is most likely also related to failure in China. Although some similarities are evident among all three countries, the findings in this study do not point toward a single, global formula for NPD success.     

Determinants of technological innovation success and failure: Does marketing innovation matter?

Innovation is attracting increasing attention from public authorities, enterprises, and academics. Although emerging evidence has indicated that marketing innovation should be regarded as critical as technological innovations for enhancing companies' competitiveness, few studies have considered this topic.This study aims to address this gap by examining the role of marketing innovation in the relationship between technological innovation and innovation success and failure. This study analyses the 2010–2012 Community Innovation Survey sample of German enterprises by using a double hurdle model and a probit model with sample selection. The results show that when enterprises undertake a technological innovation, introducing a marketing innovation is observed not to play a significant role regarding innovation success and failure. Notably, when the four types of marketing innovations are disentangled in the analysis, new findings emerge. Innovation in product packaging and design is positively related to innovation success. Innovation in product promotion is negatively related to innovation success and positively related to probability of innovation failure. Academics are called to study the role of marketing innovation, regarding innovation success and failure, by devoting their attention to the level of each marketing innovation. Enterprises should then carefully consider which marketing innovation should be introduced.     

Beating the odds in the innovation arena: The role of market and technology signals classification and noise

Innovation is a risky business. Notwithstanding the attention in research on the determinants of innovation success, the estimates of the extremely high failure rates (ranging from 40% to 90%) have not come down. As a result, new approaches have to be found to address the issues that prevent organizations from reaching innovation success over a longer period of time. In this study, Signal Detection Theory (SDT) is introduced to show that it may be less important to improve innovation practices in companies, than it is to change the nature of the projects that enter the corporate innovation funnel. In our empirical study of 44 innovation projects in the pharmaceutical and electronics industry, we show that pursuing more noisy signals (uncertain technological and market opportunities) is currently beneficial for innovation success. In general, companies allocate too few resources to noisy innovation opportunities. Interestingly, we find a positive, and not an inverted U-shaped, relationship between noise/signal ratios and innovation success. This indicates that there are almost no companies that take too much risk in the current competitive environment and that many can gain from increasing their noise tolerance. The implications from this study are quite counter-intuitive in a sense that ‘risk’ is not the cause of the innovation problems, but may be a solution.     

Commercializing Technological Innovation: Learning from Failures in High‐Tech Markets*

Commercialization is known to be a critical stage of the technological innovation process, mainly because of the high risks and costs that it entails. Despite this, many scholars consider it to be often the least well managed phase of the entire innovation process, and there is ample empirical evidence corroborating this belief. In high‐tech markets, the difficulties encountered by firms in commercializing technological innovation are exacerbated by the volatility, interconnectedness, and proliferation of new technologies that characterize such markets. This is clearly evinced by the abundance of new high‐tech products that fail on the market chiefly due to poor commercialization. Yet there is no clear understanding, in management theory and practice, of how commercialization decisions influence the market failure of new high‐tech products. Drawing on research in innovation management, diffusion of innovation, and marketing, this article shows how commercialization decisions can influence consumer acceptance of a new high‐tech product in two major ways: (i) by affecting the extent to which the players in the innovation's adoption network support the new product; (ii) by affecting the post‐purchase attitude early adopters develop toward the innovation, and hence the type of word‐of‐mouth (positive or negative) they disseminate among later adopters. Lack of support from the adoption network is found to be an especially critical cause of failure for systemic innovations, while a negative post‐purchase attitude of early adopters is a more significant determinant of market failure for radical innovations. There follows a historical analysis of eight innovations launched on consumer high‐tech markets (Apple Newton, IBM PC‐Junior, Tom Tom GO, Sony Walkman, 3DO Interactive Multiplayer, Sony MiniDisc, Palm Pilot, and Nintendo NES), which illustrates how commercialization decisions (i.e., timing, targeting and positioning, inter‐firm relationships, product configuration, distribution, advertising, and pricing) can determine lack of support from the innovation's adoption network and a negative post‐purchase attitude of early adopters. The results of this work provide useful insights for improving the commercialization decisions of product and marketing managers operating in high‐technology markets, helping them avoid errors that are precursors of market failure. It is also hoped the article will inform further research aimed at identifying, theoretically and empirically, other possible causes of poor customer acceptance in high‐tech markets.     

The characteristics of successful innovators and technically progressive firms (with some comments on innovation research)

Abstract. Parallel with the growing realization by modern economists of the role that technical change plays in economic growth there has, during the last twenty years or so, and particularly during the last decade, been an upsurge of interest in research relating to technological innovation. (Mansfield, 1968a; Minasian, 1969; Aukraust, 1969; Thurow, 1971; Mansfield, 1968b). This has led to a number of studies which have aimed at discovering factors associated with success and failure in industrial innovation and the characteristics of technically progressive firms : as a result of this, there now exists a considerable and impressive body of empirical knowledge concerning successful and unsuccessful innovators. This paper briefly reviews the results of some of the more important of these innovation studies, and attempts to highlight areas of agreement between them, both concerning factors associated with success in innovation, and factors associated with failure and delay. It then comments on some of the limitations of the studies, and offers several suggestions concerning aspects of future innovation research which might go some way towards overcoming these limitations. The paper does not pretend to offer any startlingly original data or theory (although the textile machinery results are new—see Tables 1 and 2), but rather it is intended for use as an 'innovation checklist' for the busy manager and as a preliminary guide for those who are unfamiliar with the innovation literature.