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PurposeThis paper seeks to propose a simple four‐element model for how organisations should manage their public relations when they are faced with a critical incident.Design/methodology/approachThe article brings together findings from previous research to construct a four‐element model. Five short case studies are then used to illustrate how the four elements contribute to the management of a critical incident.FindingsOrganisations need to follow four elements for their public relations when they are facing a critical incident. These four elements are: think of the public and the media; act fast; be straight; and, show concern and compassion.Practical implicationsThose organisations that used the four elements of the public relations process appear to have gained not only from the short‐term benefits of managing the incidents but also from a long‐term effect on their corporate reputations.Originality/valueThis paper is of value to senior managers and public relations professionals in that it provides a simple four‐element model for positively managing public relations in a critical incident.

AbstractPast research in the field of new product development has focused on internal issues such as management abilities and expertise, synergy, product strategies, and screening procedures. The objective of this study was to identify those characteristics relevant to new product development which are unique to decentralized regions' businesses. For this purpose a questionnaire was mailed out to 150 manufacturing companies. This study has given a new perspective to this issue since not only internal factors but also external dimensions play an important part in this process. Thus, the definition of environment which has traditionally been used must be extended to include a number of other dimensions such as the physical environment in which the company operates and the availability of an adequate work force and external support services. Moreover, the overall perception of the environment is very important because perception results in attitudes or learned predispositions to respond in an unfavorable way to doing business in peripheral regions.RésuméCette étude avait pour but découvrir dans quelle mesure les compagnies d'une région périphérique se distinguent des autres ence qui concernele développement de nouveaux produits. A cette fin, un questionnaire fut envoyé à 150 compagnies manufacturières. Cette étude a révélé que l'environnement nord‐ontarien présente certaines caractéristiques qui sont perçues comme ayant un impact négatif sur le développement de nouveaux produits: les conditions climatiques, l'éloignement des marchés, le coǔt des transports, l'insuffisance de main d'oeuvre qualifiée et l'absence d'infrastructurey jouent un rǒle déterminant. La définition de l'environnement que l'on retrouve dans les études antérieures doit donc ětre modifiée pour inclure un certain nombre d'éléments additionnels. Qui plus est, non seulement l'environnement mais sa perception par la communauté des affaires joue un rǒle déterminant dans le développement des nouveaux produits parce que la perception influence les attitudes.

Systems in the natural resource industry vary in their tolerance of human errors. Such operations are open to fallible decisions resulting from the way in which the organization deals with information. Organizations must therefore improve on their ability to learn from incidents in order to reduce the frequency and severity of errors. Presents information on fallible decisions from the management and cognitive sciences, as well as major disasters (for example Challenger; Herald of Free Enterprise). Describes a framework for increasing organizational learning through incident analysis and presents a five‐step method for systematically analysing incidents.

PurposeThe purpose of this paper is to propose a simple heuristic model that provides diagnostic capabilities and prevention insights.Design/methodology/approachThe paper brings together findings from previous research including injury statistics from several industries to illustrate that the model's predicted results can be found in practice. This is a conceptual paper that applies a simple heuristic model to existing data. The model leads to an equation with four parameters: a rate of improvement reflecting prevention, a rate of deterioration reflecting obsolescence and lapsing of procedures and practices, an intrinsic limit reflecting technological capability, and a "viscosity" that adds the impact of management system malfunction to the technological limits and normal delays.FindingsThe model says that, on the average, injury rates decrease with time if the rate of rejection is greater than the rate of mortality. If "r"<"m" injury rates increase exponentially with time, and drastic results can follow. When "r"="m" the model produces a constant rate of failure that will continue until something is done to increase "r" or decrease "m". A constant rate of failure means that an apparent safety limit has been reached. Unless this corresponds to the technological limit, a constant rate means that some preventable failures are recurring with regularity: they risk being accepted as "hazards of the job". Stable periods may be normal, but they can lead to complacency.Practical implicationsThe heuristic power of the model is evident in that parameters and insights from applying it can help define prevention activities to reduce the rate of injury and, by implication, to lengthen operational periods between consecutive injuries.Originality/valueThe drum model can help managers understand the separate but related effects of technology and management on injury rates. The model can be used to seek prevention possibilities hidden in the aggregate data, and it can help the manager to use period data to identify areas or groups in need of help.

Describes an integrated model of error management which includes: the external environment; the corporate environment; the manager and the managed; incident management; inquiries; and, learning from errors. Includes classification of error types with examples. By understanding this model organizations can improve their ability to manage error.