Search results

Demand-supply balancing (DSB) strategies and approaches are becoming increasingly important for manufacturing and operations. The purpose of this paper is to analyze practices of manufacturing companies and how they balance demand/supply in operations.

Questionnaire-based interview has been conducted at 20 largest companies having manufacturing/operations in Finland.

Supply chain structure, flexibility, demand management, capacity management, inventory management and revenue management are perceived as key practices for DSB.

The results show importance of supply chain-related parameters such as supply chain flexibility and inventory management in addition to production planning and control. The study is delimited to Finland companies but it gives an idea how decision making in operations generally can be perceived.

DSB actions should be connected to operations strategy and long-term planning of the company.

DSB is a strategic-level operations question which has an impact on several functions of supply chain.

This paper posits that arm’s length buyer‐supplier relationship as the intermediate type between market exchange relations and strategic partnership might be advisable, and information technology may have a role as a mechanism actualizing the effects of such arm’s length relationship by strategic supply‐line diversification. Based on the theoretical analysis on interactive feedback relationships among IT level, buyer‐supplier relationships, and supply chain structure, we suggest a set of advisable buyer‐ supplier relationship type for efficient supply chain management. Also, doing so would be helpful in suggesting a dynamic IT investment and adoption model appropriate for the establishment of productive buyer‐supplier relationship, and further in providing theoretical foundations and practical guidelines on the role and function of B‐to‐B E‐commerce for efficient SC integration.

The life span of an aircraft is usually around 30 years in the commercial aviation industry. During this time span, aircraft needs maintenance to stay in service. The cost of maintenance, repair and overhaul (MRO) activities in its pure nature is a significant portion of operations, accounting around 10 percent of all cost drivers. The purpose of this paper is to design/develop and critically assess a comprehensive model of operations at Turkish Technic – the MRO department of Turkish Airlines.

A comprehensive systems dynamics model is designed and developed to holistically represent and critically assess the different facets of MRO operations to help in analyzing various decision scenarios at Turkish Airlines.

The developed system dynamics (SD) model presented unique opportunities to test various MRO operations’ work load and aircraft fleet expansion policy alternatives. The model can also be used as a “learning laboratory” by altering various system parameters and testing different policies. The case study results suggested that MRO operations have a direct impact on the available number of airworthy aircrafts and hence, the usable fleet seat capacity; to sustain a profitable airline fleet, the airline companies should take into account the unique characteristics/needs of MRO operations for both existing and new/prospective aircrafts.

There are several SD studies in the literature focusing on the airline industry, but the MRO operations are virtually neglected in them. Hence, the proposed SD model contributed to the extant literature. The value of the developed model stems from its potential use in the critical analysis of decision scenarios as well as being leveraged as a training/learning laboratory.

Drawing on information processing theory, the linkage between buffering and bridging and the ability on the part of procurement to resolve demand–supply imbalances is investigated, as well as contexts in which these strategies may be particularly useful or detrimental. Buffering may be achieved through demand change or redundancy, while bridging may be achieved by the means of collaboration or monitoring.

This study employs a hierarchical regression analysis of a survey of 150 Finnish and Swedish procurement and sales and operations planning professionals, each responding from the perspective of their own area of supply responsibility.

Both the demand change and redundancy varieties of buffering are associated with procurement's ability to resolve demand–supply imbalances without delivery disruptions, but not with cost-efficient resolution. Bridging is associated with the cost-efficient resolution of imbalances: while collaboration offers benefits, monitoring seems to make things worse. Dynamism diminishes, while the co-management of procurement in S&OP improves procurement's ability to resolve demand–supply imbalances. The most potent strategy for tackling problematic contexts appears to be buffering via demand change.

The results highlight the importance of procurement in the S&OP process and suggest tactical measures that can be taken to resolve and reduce the effects of supply and demand imbalances.

The results contribute to the procurement and S&OP literature by increasing knowledge regarding the role and integration of procurement to the crucial process of balancing demand and supply operations.

Houses are durable, so an imbalance between demand and supply occurs after time has passed since initial construction. The purpose of this study is to quantify the extent of this imbalance for existing houses, focusing on the heterogeneity across property segments.

This study uses a unique data set on the “inquiry volume” that each property received from an online real estate portal to measure the volume of demand in relation to supply. Simple regressions are conducted in the resale condominium market across the Tokyo metropolitan area.

The inquiry volume successfully tracked a recent expected trend in which demand relative to supply is stronger for condominiums in reasonably priced areas, condominiums in convenient, accessible locations, condominiums built within the last 20 years and compact and spacious units. This study also confirms that these trends cannot be captured through heterogeneity in price levels, which has been widely used in previous studies on measuring housing preferences.

As an indicator of conditions in the housing market, the property-level inquiry volume has strong potential to provide useful information for supply strategies and for the sustainable use of existing housing stocks.

The originality of this paper is the use of information on the buyer side, which is typically unobservable.

The purpose of this paper is to seek an efficient method to tackle the energy provision problem for smart grid with sparse constraints and distributed energy and storage devices.

A complex smart grid is first studied, in which sparse constraints and the complex make-up of different energy consumption due to the integration of distributed energy and storage devices and the emergence of multisellers are discussed. Then, a real-time pricing scheme is formulated to tackle the demand response based on sparse bilevel programming. And then, a bilevel genetic algorithm (BGA) is further designed. Finally, simulations are conducted to evaluate the performance of the proposed approach.

The considered situation is widespread in practice, and meanwhile, the other cases including traditional model without the sparse constraints can be seen as its extensions. The BGA based on sparse bilevel programming has advantages of “no need of convexity of the model.” Moreover, it is feasible without the need to disclose the private information to others; therefore, privacies are protected and system scalability is kept. Simulation results validate the proposed approach has good performance in maximizing social welfare and balancing system energy distribution.

In this paper, the authors consider the sparse constraints due to the fact that each user can only choose limited utility companies per time slot. In reality, there exist some other sparse cases, which deserve further study in the future.

To the best of the authors’ knowledge, this is one of the very first studies to address pricing problems for the smart grid with consideration of sparse constraints and integration of distributed energy and storage devices.

The purpose of this paper is to understand how companies design sales and operations planning (S & OP) contingent on the planning environment (PE).

On the basis of the literature, the paper creates an analytical framework identifying the main constructs related to the PE and S & OP design, which is the basis for gathering and analysing qualitative data from eight cases in the food industry. The findings highlight the relations between S & OP and the PE, and are used for generating three propositions.

Responding to the complex and uncertain PE, the companies set up S & OP on a stock-keeping unit (SKU) level, with the possibility of re-planning and a flexible planning horizon, thus differing from what has generally been suggested in the literature. In addition, the companies are aligning the inputs, activities, and outcomes of the S & OP process to the PE. Particularly important environmental contingencies are uncertainty connected to demand and supply, frequent product launches, and production network complexity. Product-related variables have a lower impact on the S & OP design.

The present study is limited to one industry only and a comparison between industries with larger data sets would be valuable in future studies. The study selected cases based on their S & OP maturity; further studies need to explore the effect of the alignment of S & OP and the PE on the planning performance.

In the literature, S & OP is presented as a generic process with a strict formal design that is equal for all companies. The study provides insights into how companies adjust S & OP according to the PE.

The purpose of this paper is to propose a “Fit” manufacturing paradigm for industry so that manufacturing companies can become economically sustainable and can operate effectively in a global competitive market. The proposed Fit paradigm is aimed at providing a new manufacturing management perspective to both academics and industrialists.

The Fit paradigm is developed and proposed as a new manufacturing management strategy towards creating economically sustainable manufacturing organisations. Fit is a theoretical development using the principles of existing manufacturing paradigms along with new and innovative management concepts to create a sustainable approach to manufacturing.

Manufacturing strategies such as lean and agility allow companies to deliver bottom‐line savings in production terms although their effectiveness depends upon the volume and demand profile of their products. The trend towards mass customisation requires companies to provide personalised products and services at mass production prices. This now places a further burden on companies and therefore a holistic manufacturing framework must be developed in order to ensure that the factory of the future is able to meet this new demand. This paper proposes a fit manufacturing paradigm which integrates the manufacturing efficiencies achieved through lean and agility with the need to break into new markets through effective marketing and product innovation strategies to achieve long term economic sustainability. The small scale application of the approach in a case company shows that the initial results to be positive when measured against a fit index which is developed within this paper.

The development of a fit paradigm aimed at tackling directly the issues of economic sustainability is proposed and is considered by the authors as one of a kind. Fit will also provide a framework for the implementation of sustainable manufacturing operations within organisations.

Today, most of the car manufacturers world-wide have embraced the principles of lean manufacturing on strategic and operational level. On strategic level car companies like Toyota (Womack et al., 1990) shifted 63 per cent of the value of the car towards the first, second and third tier suppliers for the co-production and co-development of cars as an effect of lean implementation. However, lean implementation was also followed by for instance Ford and GM in the USA, the latter company faced a sudden disruption in 2009 due to the break-out of the financial crisis in 2008, while Ford survived. Could this be foreseen? The exclusive use of (classic) financial performance indicators may give a false image of a company’s current and future performance. There is a need for a model to identify “the stars and the laggards’ regarding car companies by taking into account non-financial and intangible dimensions as advocated by Neely et al. (2003) regarding the third generation of business performance measurement systems. The purpose of this paper is therefor to propose a method to measure and benchmark car company performance which includes the non-financial R&D dimension as well as supply chain, value creating and employee dimensions. These dimensions are present in the value leverage model (van Blokland et al., 2012a, 2012b) which can serve as a basis for this method. The aim is to contribute to the third generation business performance measurement systems by further development of the value leverage model towards a maturity model for benchmarking car company performance. The proposed method can provide a big picture and give insight regarding company performance and direction of the performance.

Value leverage can be measured by a correlation analysis regarding three dimensions, namely, supply chain, R&D and value creation, all relative to the employee or capita which results in the average value leverage (AVL) factor. This AVL factor can be used to compose a combined relative and absolute ranking. The score regarding the AVL results in a relative ranking expressing the level of stability regarding the car companies value chain and system. For the absolute ranking the car companies receive per variable parameter a score according to their absolute performance relative to the other car companies. The relative and absolute ranking are presented on the vertical and horizontal axes forming a matrix. The matrix is the basis for the stability-value leverage maturity model for measuring and benchmarking company performance. With the proposed method, the following main research question can be answered: “How can company performance be measured and benchmarked from a stability-value leverage perspective?”.

With the proposed method, stability-value leverage performance can be measured. The relative ranking on the vertical axis and the absolute ranking form together a matrix which is presented by a scatterplot. A matrix with four maturity levels emerged from the analysis by introducing the average score of all the car companies together in the data set crossing the matrix vertical and horizontal. The four levels are as follows: Level I, low stability – low value leverage; Level II, low stability – high value leverage; Level III, high stability – low value leverage; and Level IV, high stability – high value leverage. Stability-value leverage performance of car companies can be measured over time which makes it possible to observe to which direction the car company migrates for instance from Level I to Level III, before and after the financial crises in 2008. The car companies BMW, Daimler, Audi, Ford and Honda are the best performing companies in stability-value leverage over the period 2000-2014, as they are situated at Level IV. With the findings, the main research question can be answered. The value leverage indicators can be used for measuring and benchmarking company performance regarding four maturity levels of stability and value leverage. The direction of performance can be observed as well.

This research is limited to the car industry. Further research is devised to test the indicators for instance on the truck manufacturing industry. Further research towards new variables is part of the ongoing research.

With the value leverage maturity model, it is possible to inform stakeholders about stability, value leverage and value creation capability of car companies. Weak performing companies can be identified in an early stage with this method to anticipate for instance on possible discontinuation of a car company effecting in merger an acquisition processes.

With the method stakeholders such as employees, users of cars and investors can be informed about how and why car companies perform in an unstable or stable manner.

This research towards ranking and classification of car companies aligns with theories regarding lean manufacturing and maturity models, as these models are used to compare companies on their level of perfection or excellence.