Search results

The present study considers how clothing and shoe retailers in New Zealand, Portugal and Hungary manage promotion campaigns and looks at the objectives that are most important to these retailers as well as the marketing activities that are undertaken to reach these objectives. Change‐of‐season sales are found to be the most frequently used sales type by the retailers studied and these sales are linked with objectives of moving a volume of stock and activities such as co‐ordination of media across all forms. Secondary sales types include Christmas and general sales, and these are linked with other promotional objectives and activities such as increasing profit and dollar sales, and stock management.

There have been numerous extensions of the maximum covering location problem that has been developed in the last decade to deal with facility location. Most of the research, however, addresses a single attribute or objective. In the case when a single criterion such as minimizing average response time to access a service facility is insufficient to address the interests of the decision maker, multiple objectives must be employed. Qualitative factors like customer service and market demand as well as quantitative factors like distribution and operating costs need to be appropriately weighted and used in a mathematical programming model. We develop a multi‐objective model for a service facility location problem that simultaneously sites facilities and allocates demand for products from different customer zones. We apply this model to “real‐world” data and show the practical advantages of using this model to solve capacitated service logistics problems.

This article seeks to review how objectives are conventionally designed for organizations before detailing a new and proven approach based on the author's many years of research and consulting experience. The practical situation on which the article aims to focus is strategic planning, a process in which CEOs, middle managers and directors on boards find themselves frequently involved.

The outlined objective‐setting methodology is the result of more than two decades of action research. The author has worked with organizations across all sectors – private, public and not‐for‐profit – to develop meaningful and measurable objectives during the course of designing their strategic plans.

Most organizations flounder when it comes to objective setting. They come up with lists of objectives that are a mixture of quantified and non‐quantified items or restatements of mission, vision and values; they are often vague and general and are assembled as one undifferentiated block, i.e. not segmented according to an organization's key stakeholders. No wonder managers find the conventional process of objective‐setting both frustrating and ineffective. In contrast, the author has found that the approach outlined in this article engages participants and produces clear and measurable outcomes.

Organizations in all sectors – business, government and not‐for‐profit – can benefit greatly by re‐thinking their current practices and changing the way they go about designing their objectives. The approach outlined herein has solved many conceptual and practical problems managers face and led to the design of organization objectives that really shape precise strategies.

The purpose of this paper is to explore why objective setting is often found difficult and consider what to do about it. The paper critically assesses the two main managerial perspectives on objective setting before summarising evidence-based research on what works. Based on this literature review, the paper develops a contingency model of objective setting. It then describes how to use this model in practice.

The paper uses a review of the managerial and evidence-based literature on objective setting to develop a contingency model of objective setting. It describes how this model is operationalised by developing a scale to measure the differences between jobs and the situations they operate in. The model is represented diagramatically. Guidance is given on how to use the model in practice.

Result-centred and process-centred approaches to objective setting are described and critically assessed. Evidence-based research describing the relationship between objective setting and performance is also presented. In general, clear and specific goals that are challenging but realistic have a moderate effect on performance. However, this only holds for straightforward and predictable tasks. When prior knowledge is needed to perform a task or when the task is complex, a general goal, behavioural goal or learning goal is more effective. Parallels between the managerial perspectives and the contrasting situations form the basis of a contingency model of objective setting.

The relevant theory is described and critically examined. This provides useful descriptions of two different ways to go about setting objectives. The conclusions of recent studies and reviews using evidence-based research are described. They establish both what works and when it works. Taken together, these insights provide a foundation on which to develop a contingency model of objective setting.

There is no one right way to set objectives. Different situations require different approaches. It is possible to assess situations and establish the appropriate combination of perspectives. It is then possible to develop an appropriate set of objectives for the situation. Guidance is given on how to use this approach in practice. The overall approach is rooted in theory and evidence-based research.

The application of this model in the workplace can help individuals to perform more effectively. It can also help line managers, learning and development specialists, and human resource professionals to help individuals to perform more effectively. In so doing, the model helps organisations to function more effectively. This has wider implications for the economy and society.

The paper is original in that it brings together both management theory and evidence-based research to develop a contingency model of objective setting. This model as a whole and the method of assessing job characteristics are original.

Examines organizational objectives when conducting quality planning and how different planning objectives are related to its perceived performance. The sample included 42 firms representing five different planning objective orientations. Four distinct cluster groups emerged. The four orientations were named as “strategic impact and communication”, “product/process improvement”, “co‐ordination”, and “no clear objectives”, based on the interpretation of the planning objectives that loaded on each respective factor. The results suggest that certain quality planning objectives were associated with significantly higher perceived performance and the level of planning sophistication only influenced the planning performance of some groups.

The purpose of this paper is to realize a multi‐objective location‐routing network optimization in reverse logistics using particle swarm optimization based on grey relational analysis with entropy weight.

Real world network design problems are often characterized by multi‐objective in reverse logistics. This has recently been considered as an additional objective for facility location problem or vehicle routing problem in reverse logistics network design. Both of them are shown to be NP‐hard. Hence, location‐routing problem (LRP) with multi‐objective is more complicated integrated problem, and it is NP‐hard too. Due to the fact that NP‐hard model cannot be solved directly, grey relational analysis and entropy weight were added to particle swarm optimization to decision among the objectives. Then, a mathematics model about multi‐objective LRP of reverse logistics has been constructed, and a proposed hybrid particle swarm optimization with grey relational analysis and entropy weight has been developed to resolve it. An example is also computed in the last part of the paper.

The results are convincing: not only that particle swarm optimization and grey relational analysis can be used to resolve multi‐objective location‐routing model, but also that entropy and grey relational analysis can be combined to decide weights of objectives.

The method exposed in the paper can be used to deal with multi‐objective LRP in reverse logistics, and multi‐objective network optimization result could be helpful for logistics efficiency and practicability.

The paper succeeds in realising both a constructed multi‐objective model about location‐routing of reverse logistics and a multi‐objective solution algorithm about particle swarm optimization and future stage by using one of the newest developed theories: grey relational analysis.

Focuses on the nature of marketing objectives and on facets of their time‐relatedness, flexibility and consistency. Compares the nature of the objectives as between domestic and export markets, and US and UK markets. Concludes that there is very little difference between UK and US markets, although the US organizations tend to have longer term objectives, which shows them in a more favourable light.

Before considering the need to define behavioural objectives it is useful to consider the reasons for undertaking any form of training. The basic reason may be stated in terms of equipping the trainee with the skills, knowledge and attitudes necessary to perform a job or a task. Any training programme, therefore, should be constructed with this purpose in mind. In order to construct a programme along these lines it is essential that the relevant skills, knowledge and attitudes be expressed in such a way as to allow their measurement. Once this has been done a criterion is established whereby it becomes possible to evaluate the success or failure of the training programme. The measurable expression of the aims of training is what is referred to as the objectives. Inherent in the construction and expression of these objectives is a relationship to the evaluation of the training. It is, therefore, virtually impossible to consider objectives in the absence of evaluation. Returning to the basic purpose of training, it can be seen that the objectives must also be closely matched to the training needs in any situation. Thus, before objectives can be established, it is necessary to identify training needs and express them in terms of skill, knowledge and attitude requirements.

“What benefits did you derive from your teacher training course?” enquired a distinguished Head of Department. “Teaching by objectives”, I replied. “And do you teach by objectives?” was his next question, to which I answered a definite yes. But can we really claim that we all do in fact teach by objectives?

This article argues that the conflict between marketing and production can only be resolved by an understanding and recognition of the extent to which marketing influences and is dependent on the production function. It further argues that this understanding must begin during the planning process, when areas of joint responsibility (e.g. for setting stock levels) are identified and responsibility is jointly assigned for establishing objectives which are vertically and horizontally compatible. A classification system to assist the process of understanding the nature of objectives is put foward, and a theory of objective sets to assist the development of rational planning and review procedures is developed. The classification system and the theory have general applicability as well as specific value in facilitating and integrating marketing planning at strategic, tactical and operational levels.