An efficiency-based approach on human resource management: a case study of Tainan County fire branches in Taiwan.

Introduction

Disaster prevention defines three major missions: fire prevention, disaster rescue and emergently medical service relating to the lives of people. (1) People expect that the fire department can adopt proper countermeasures for disaster prevention and they also hope that fire branches can dispatch rescue teams efficiently to execute their missions. Currently, the performances of fire branches commonly adopt single or few rules to measure the performances of fire prevention, hazardous materials management, disaster rescue and duty supervision, but emergently medical services, educational training, fire investigation and general administration are not taken into consideration. Current performances tend to cause arguments because of lacking objectivity and justice. Therefore, the most important thing to do is to look for a proper measure with objectivity and justice to evaluate the performance efficiencies of fire branches and then adjust reasonable resources for those inefficient fire branches.

In 1978, Harry pointed out that efficiency, effectiveness and productivity are three major parts of performance. (2) In 1988, Fortuin (3) placed the organizational goal in two categories: efficiency and effectiveness. The efficiency is defined as the ratio between input and output, (4) and the effectiveness is defined as the achieving level of the expected production output by a production system. (5) In fact, efficiency and effectiveness represent different levels of performance, and there is no guarantee that both of them can be achieved simultaneously. However, an efficient organization must handle both of them well, and use the most efficient way to pursue maximum effectiveness. (6)

There are many measures of performance evaluation: the Ratio Approach, the Regression Analysis, the Multiple Criteria Analysis, the Analytic Hierarchy Process, the Balanced Scorecard, the Delphi Hierarchy Process, the Total Factor Productivity (TFP), and the Data Envelopment Analysis (DEA). (7) Among these methods, the DEA is the most suitable way to measure the performance efficiency of nonprofit organizations because of its multi-indication character. The performance efficiencies of fire branches have to be reasonably measured by multiple inputs and outputs, and the function relationship between inputs and outputs are unknown in advance. (8) In this research, DEA is selected as the measuring method of performance efficiencies for fire branches because of its characteristic of multi-indication, and thus the relative efficiency of each fire branch can be determined by comparing the quantitative data of inputs and outputs. (9)

The Data Envelopment Analysis (DEA) was proposed from Charnes, Cooper and Rhodes in 1978. Originally, the DEA is applied to measure the performance efficiency of the public or nonprofit organization, but later is applied to many beneficial organizations. The model of DEA is shown by the ratio of output/input and has the same meaning of the so-called TFP. (10) The DEA is based on the concepts of Pareto Optimality and Frontier to calculate the relative efficiencies of the whole decision making units (DMUs) in order to determine their performances, especially for the similar decision making units. (11) In fact, the DEA uses the separated programming via the fractional programming and then transfers the process to linear programming in order to find out the values of the relative efficiencies for the whole decision making units (DMUs) and to determine the inefficient DMUs. (12) This study is trying to measure the relative efficiency for each fire branch under the double duties of disaster prevention and the security of peoples' life and property. Besides, not only can the DEA strengthen the justice on the judgment of performance efficiency for each fire branch and provide an excellent referenced guideline for the resource allocation of each fire branch, but it also can offer the new thinking to measure the performance efficiencies of fire branches.

This study aims to assess the performance efficiencies of fire branches by using 35 fire branches of Tainan County Fire Bureau as an example. Currently, the Tainan County Fire Bureau consists of office duty and field duty sectors, including six sections, one fire center, three fire corps and 35 fire branches. The employees in the fire branch are regarded as long-term workers (13) because each fire branch has to operate all day, and thus the employees in the fire branch should be trained to handle multiple tasks, including water supply, etc. According to relevant laws and ordinances, the manpower of the fire branch is arranged relative to the population and the size of the area. (14) The current allocation of fire protection resources merely considers the location and its associated response time. (15)

The resource allocation for each fire branch has no rules to be followed, and the current allocation depends on the resource distributor; the differing characteristics of the city and country, the governmental budget subsidiaries and the scale of fire branch are not considered. Therefore, the current method often causes a biased assessment of performances. This study, however, considers the aspects of control area, loadings on fire duties and government budget in order to establish a reasonable method to assess the performances of fire branches.

The DEA is conducted in the first-stage of this study. The second stage, according to the future estimated trend of output to select a proper strategy, is (ORA)--where output trend is steady or decreasing--which is also called or Multi-Stage Resource Allocation Approach (MSRAA). In MSRAA, output tendency is increasing. The solutions of ORA are recommended from the contribution index of each input item. The MSRAA is a quantitative approach presented in this study to allocate resources and will be then described in detail in this study. Through the two approaches of ORA and MSRAA, the decision maker can adopt different strategies based on the assessment of the future output trend. Furthermore, these two strategies will function as a referenced guideline to resolve the long-term existing difficulties in a way that reasonably eliminates or allocates resources while making decisions.

The Determination of Input and Output Items

This study focuses on the investigation of the performance efficiency for each fire branch; the production function of DMU is not assumed, so that the DEA is chosen as the assessing measure of performance efficiency in this study. In fact, the DEA includes two different models: Charnes, Cooper and Rhodes, and Banker, Charnes and Cooper. Both of them have two options--input orientation and output orientation. Because a fire branch tries to minimize its input usage of resources to maintain current performance, this study adopts the input-oriented model of Charnes, Cooper and Rhodes to conduct the efficiency analysis for each fire branch. In 1989, Golany and Roll thought that the selection of input and output items was very important while executing DEA. (16) Generally speaking, the determination of the input and output items for the DEA model should be paid more attention. So, the common way to determine the input and output items is to interview with organization officers and then to analyze the organization and management objectives, literature reviews, and experiences. (17)

Therefore, four input items (the number of on-duty personnel, the on-duty cost, the total vehicle displacement and the vehicle maintenance fee) and five output items (the number of fire cases, the number of rescue cases, the number of public service cases, the number of listed fire protected spaces and the number of fire hydrants) were selected as variables in this article for assessing efficiency.

The definition of each variable is given in table 1, and the input and output values for each DMU are listed in table 2. Table 3 describes the correlation coefficiencies between input items and output items of DMUs. From table 3, there exist positive correlations between each input item and each output item. This means that the relationship between each variable complies with the characteristic of "isotonicity," which is the basic assumption of Data Envelopment Analysis. Backward elimination (18) can then be applied in order to delete the input and output items with zero weight in sequence until the weight of each left item is nonzero (i.e. if the weights of input/output items are zero, those items are eliminated). After executing the backward elimination, the previous selected items cannot be deducted from this study. The weights of input and output items for each DMU are listed in table 4.

Empirical Analysis

Frontier software was applied to investigate 35 fire branches of Tainan Fire Bureau in Taiwan by using the input and output data from 2003 to perform the efficiency analysis and potential improvement analysis. The efficiency analysis is described below.

The production efficiency derived from the Charnes, Cooper and Rhodes model of DEA includes the technical efficiency and the scale efficiency. The production efficiency, the technical efficiency, the scale efficiency and the return to scale of each fire branch in Tainan County are listed in table 5. For example, the production efficiency of Baihe branch is 0.6656, its technical efficiency is 0.6775 and the scale efficiency is 0.982. It reveals that the production inefficiency of Baihe branch is mainly due to its technical factor because its technical efficiency (0.6775) is smaller than the scale efficiency (0.982). The analyzing results of DEA for those 35 fire branches in Tainan County are described as follows: