Agglomeration economies and vertical alliances: the route to product innovation in biotechnology firms

This paper develops and tests hypotheses related to the aggregated effect of geographic clustering and cooperation networks positively affects the innovation performance. It is argued that clusters and alliances may represent micromechanisms that improve access to critical resources and competences on which innovation capability is based (such as spillovers, downstream competences and finance). By analysing survey data from a sample of biofirms, important insights are found into the benefits of being located within a cluster and collaborating with specific types of partners.     

Getting beyond ‘grin and bear it’ in the practice of risk management

Risk perception researchers frequently notice major discrepancies between expert judgment and lay opinion concerning the identity of ‘large’ risks. These discrepancies are particularly disconcerting because they lead to a significant misallocation of scarce resources devoted to public risk management. Yet, democratic decision-making also appeals to many risk perception researchers, and some see such little prospect for a solution thaty they seem close to surrendering to decision-making based on lay risk perception. This article argues that such a ‘grin and bear it’ strategy is also unsatisfactory; that risk perceptions are unstable grounds for decision-making; that expert risk assessment and lay risk perception differ by design rather than accident; that risk experts' search for ‘virtuous lawmakers’ who would make public decisions for the greatest public good is a vain one; that the dissonance risk perception researchers now observe will likely get worse in the new information age; and that risk perception researchers need to return to first principles to find solutions to these dilemmas. In particular, the gap between expert judgment and lay perception will close only when non-experts are permitted and expected to make their own risk management decisions, so far as that is possible, while bearing full responsibility for their choices.     

Innovation capability in Australian manufacturing organisations: an exploratory study

This paper reports on the results of a comparative case study of innovation capability in Australian manufacturing companies. Following a review of the salient literature in the field, six case studies were undertaken with organisations having a degree of variance across company size, ownership type and industry sector. All the cases reflected a history of successful innovation and the managers were interviewed about the attributes of innovation and the ways in which sustained innovation was manifested in their organisations. Based on the interview data, a model of innovation capability was developed with a view to identifying attributes common to systematic and sustained innovation. These companies derived competitive advantage from differentiation through their innovation. The implications of the model for manufacturing organisations in general, and their managers in particular, are subsequently discussed.     

Technology-mining model concerning operation characteristics of technology and service providers

Owing to the high variety of industry development, technology and service providers (TSPs) are dedicated to the development of applied technologies. The operation purposes of these service providers are to provide customized services and technologies that meet the various client requirements and improve the capability of their clients via various projects. To outreach services to related enterprises successfully, the TSPs need an effective approach to explore the technology demands of enterprises. Based on the client demands, TSPs can establish effective operation strategies and technology development direction. Previously, the technology-development strategies are determined by domain experts or sales through trial and error. With regard to the operation requirements of the TSPs, this paper presents a technology-mining model based on their contract/project history. The aims of the proposed model focus on exploring technologies with higher client demands and significant research and development returns so that the TSPs can effectively expand and continue their business. Furthermore, the promotion sequence of different technologies can also be determined via the proposed-mining model. By application of the technology-mining model, effective suggestions can be provided to the TSPs for business extension.     

Network variations at the intersection of national capability orientation and technological path dependence – patent citation network analysis of the hydrogen energy and nano-tech sectors

How do national factors intersect in network formation in different emerging sectors? Scholars have focused on these regarding networking phenomena: the effects of national and sectoral factors. In spite of their theoretical contributions, attempts have been neglected in identifying and/or linking the factors from both national and sectoral innovation systems within the networks. This paper examines the cross-country differences within a sector, and the cross-sectoral differences within a country, as the consequences of sectoral–national intersections. Longitudinal patent citation networks in two emerging sectors, the hydrogen energy sector and nano-tech sector have been analysed for a time period from 2004 to 2012, in four diverse developed countries. The results convey that the two sectors demonstrate significantly varied networking activities, notably influenced by national capability orientations. On the other hand, cross-country differences in networking activities are also varied by technological path dependence.     

Towards a general theory of driver behaviour

Taylor [Taylor, D.H., 1964. Drivers' galvanic skin response and the risk of accident. Ergonomics 7, 439-451] argued that drivers attempt to maintain a constant level of anxiety when driving which Wilde [Wilde, G.J.S., 1982. The theory of risk homeostasis: implications for safety and health. Risk Anal. 2, 209-225] interpreted to be coupled to subjective estimates of the probability of collision. This theoretical paper argues that what drivers attempt to maintain is a level of task difficulty. Naatanen and Summala [Naatanen, R., Summala, H., 1976. Road User Behaviour and Traffic Accidents. North Holland/Elsevier, Amsterdam, New York] similarly rejected the concept of statistical risk as a determinant of driver behaviour, but in so doing fell back on the learning process to generate a largely automatised selection of appropriate safety margins. However it is argued here that driver behaviour cannot be acquired and executed principally in such S-R terms. The concept of task difficulty is elaborated within the framework of the task-capability interface (TCI) model, which describes the dynamic interaction between the determinants of task demand and driver capability. It is this interaction which produces different levels of task difficulty. Implications of the model are discussed regarding variation in performance, resource allocation, hierarchical decision-making and the interdependence of demand and capability. Task difficulty homeostasis is proposed as a key sub-goal in driving and speed choice is argued to be the primary solution to the problem of keeping task difficulty within selected boundaries. The relationship between task difficulty and mental workload and calibration is clarified. Evidence is cited in support of the TCI model, which clearly distinguishes task difficulty from estimates of statistical risk. However, contrary to expectation, ratings of perceived risk depart from ratings of statistical risk but track difficulty ratings almost perfectly. It now appears that feelings of risk may inform driver decision making, as Taylor originally suggested, but not in terms of risk of collision, but rather in terms of task difficulty. Finally risk homeostasis is presented as a special case of task difficulty homeostasis.     

Perception of traffic risks for older and younger adults

The study examined differences in the perception of traffic risks for older and younger adults. Thirty-four younger participants (mean age 24.7 years) and 30 older participants (mean age 70 years) estimated the number of younger and older people (out of 100,000 people) that were injured in car and pedestrian crashes in a recent year. Both age groups viewed older adults’ risks in pedestrian crashes as higher than those of younger adults, and saw older adults’ risks in car crashes as identical to the risks for younger adults. Both age groups assessed the risks for their own group quite accurately, but erred in their assessment of the risk for the other group. Older participants tended to overestimate the risk for younger adults, and younger participants tended to underestimate the risk for older adults. These results point to the need to enhance awareness of the age-related increase in traffic risk, which could potentially promote more considerate driving behavior.     

Cyclists' perception of risk in roundabouts

Converting an intersection into a roundabout improves motor vehicle safety, but a similar safety effect is not found for car–bicycle collisions. Very little is known about the reasons behind these collisions. In this study a first step towards an understanding of the reasons behind these collisions is taken. The study focuses on cyclists’ perceived risk in specific situations, factors influencing the perception of risk and cyclists’ knowledge about traffic rules regulating the interaction between road users in roundabouts.

One thousand and nineteen cyclists aged 18–85 participated in the study. Data were collected using structured interviews conducted in five Danish roundabouts.

Underestimation of risk and lack of knowledge about relevant traffic rules may contribute to car–bicycle collisions in roundabouts. Cyclists prefer road designs with a clear regulation of road user behaviour. A need to increase knowledge about traffic rules regulating road user behaviour in roundabouts is identified.     

Data mining techniques for customer relationship management

Advancements in technology have made relationship marketing a reality in recent years. Technologies such as data warehousing, data mining, and campaign management software have made customer relationship management a new area where firms can gain a competitive advantage. Particularly through data mining—the extraction of hidden predictive information from large databases—organizations can identify valuable customers, predict future behaviors, and enable firms to make proactive, knowledge-driven decisions. The automated, future-oriented analyses made possible by data mining move beyond the analyses of past events typically provided by history-oriented tools such as decision support systems. Data mining tools answer business questions that in the past were too time-consuming to pursue. Yet, it is the answers to these questions make customer relationship management possible. Various techniques exist among data mining software, each with their own advantages and challenges for different types of applications. A particular dichotomy exists between neural networks and chi-square automated interaction detection (CHAID). While differing approaches abound in the realm of data mining, the use of some type of data mining is necessary to accomplish the goals of today’s customer relationship management philosophy.     

Manufacturing knowledge management strategy

The study sought to understand the components of knowledge management strategy from the perspective of staff in UK manufacturing organizations. To analyse this topic, we took an empirical approach and collaborated with two manufacturing organizations. Our main finding centres on the key components of a knowledge management strategy, and the relationships between it and manufacturing strategy and corporate strategy. Other findings include: the nature of knowledge in manufacturing organizations; the relevance of (in)formal processes; top-down and bottom-up communication; taking ownership for information processes. We also make comments on the development of action plans for better knowledge management. The implications are that, for an integrated approach to knowledge management strategy in manufacturing organizations, involvement across the organization and at all levels is necessary.     

Total customer satisfaction as a business strategy

There are two fundamental goals which are universal in business. The first is to grow market share, and the second to grow profits. In order to accomplish these goals, the company must differentiate itself from its competitors, in the customer's view, in one or more of the five following areas: (1) price, (2) delivery, (3) performance, (4) quality, (5) total customer experience. Stressing one area of differentiation to the exclusion of the others will not achieve the goals. For example, in stressing price alone, a company has defined its products as a commodity and as Dev Dion of the Strategic Planning Institute once said, ‘The producers of commodities reap commensurate rewards.’ Similarly, stressing fast delivery of a product of poor quality, or stressing superior quality for a product providing marginally useful performance are both losing strategies. The only strategy I know of which provides equally balanced focus on all five major areas of differentiation is total customer satisfaction, as the fundamental objective of the company. Bob Galvin, when Chairman of Motorola, summed it up by saying, ‘If you take care of the customer better than any of your competition, the business will take care of itself.’ In saying this, however, he meant not only the product, but all of the other ways in which you and the customer interact.     

Knowledge elicitation for risk mapping in concurrent engineering projects

Concurrent Engineering aims to incorporate the overlapping of processes in order to reduce its time-to-market and thereby sustain the existence of organizations in increasingly competitive times. Although faster product design, development, and delivery are the intended outcomes of concurrent engineering, one of the undesirable by-products is an increase in risks as a consequence of uncertainties between interdependent processes. Hence, the risks need to be identified, assessed, and mitigated together with concurrent engineering considerations for the elimination of the ‘domino-effect’ within risk management. This paper concentrates primarily on knowledge elicitation techniques that were used to provide information to the Intelligent Risk Mapping and Assessment System (IRMAS?) to identify, prioritise, analyse, and assist project managers to manage perceived sources of CE risks. Techniques such as expert interviews, brainstorming, the Delphi technique, and the analogy process are discussed in relation to compiling the knowledge used for this expert system. A total of 589 risk items were identified for different project types, and information on 4372 items and 136 lessons learned were collected from experts at HdH. The core of the research is a reasoning methodology used for Knowledge Elicitation of a Risk Mapping and Assessment System which will not only support the decision-making process of the user but also aid the knowledge retrieval, storage, sharing, and updating process of manufacturing organizations. This research provides a systematic engineering approach to risk management of concurrent product and process development.     

Critical factors and paths influencing construction workers’ safety risk tolerances

While workers’ safety risk tolerances have been regarded as a main reason for their unsafe behaviors, little is known about why different people have different risk tolerances even when confronting the same situation. The aim of this research is to identify the critical factors and paths that influence workers’ safety risk tolerance and to explore how they contribute to accident causal model from a system thinking perceptive. A number of methods were carried out to analyze the data collected through interviews and questionnaire surveys. In the first and second steps of the research, factor identification, factor ranking and factor analysis were carried out, and the results show that workers’ safety risk tolerance can be influenced by four groups of factors, namely: (1) personal subjective perception; (2) work knowledge and experiences; (3) work characteristics; and (4) safety management. In the third step of the research, hypothetical influencing path model was developed and tested by using structural equation modeling (SEM). It is found that the effects of external factors (safety management and work characteristics) on risk tolerance are larger than that of internal factors (personal subjective perception and work knowledge & experiences). Specifically, safety management contributes the most to workers’ safety risk tolerance through its direct effect and indirect effect; while personal subjective perception comes the second and can act as an intermedia for work characteristics. This research provides an in-depth insight of workers’ unsafe behaviors by depicting the contributing factors as shown in the accident causal model developed in this research.