Yuhchang Hwang

An Empirical Investigation of the Relationship between Intellectual Capital and Firms’ Market Value and Financial Performance

The objective of this paper is to investigate the relationship between the value creation efficiency and firms’ market valuation as well as financial performance, using data drawn from Taiwanese listed companies. Our results support the proposition that intellectual capital has a positive impact on corporate market value and financial performance, and may be a leading indicator for future financial performance. In addition, we also found investors may place different value on the three components of value creation efficiency (physical capital, human capital and structural capital). Finally, our results suggest that R&D expenditure may capture information on structural capital and has a positive effect on firm value and profitability.

The Performance Effects of Congruence Between Product Competitive Strategies and Purchasing Management Design

The objective of this study is to examine a performance contingency effect between product competitive strategy and organization design using an archival approach. Specifically, this study examines a sample of 194 firms from 20 industries based on the data collected by Center for Advanced Purchasing Studies (CAPS) in its benchmarking surveys between 1989-1994 and links the benchmarking data to the COMPUSTAT (Standard & Poors) financial data of these firms. The results of the study reveal a contingency relationship among product competitive strategies, purchasing design characteristics, and overall firm financial performance (return on assets). Specifically, the nature of this contingency relationship suggests that a firms product competitive strategy must be enabled with a complementary design in purchasing management to promote firm performance. Given the growing practice of benchmarking at the functional level, this study also examines whether or not a firm achieving a congruency in product strategy and design will necessarily enjoy higher operational efficiency at the purchasing management level. The results show that this is true only under specific conditions. The implications of the preceding findings are discussed accordingly.

Measurement and sources of overall and input inefficiencies: Evidences and implications in hospital services

Abstract Traditional data envelopment analysis (DEA) focuses exclusively on measuring the overall efficiency of a decision making unit (DMU). Yet, variables that have explanatory power for the overall operational inefficiency of a DMU may not necessarily be the same as those that affect its individual input inefficiencies. On many occasions, variables that explain the overall inefficiency of a DMU can be inconsistent or incongruent with those that cause its individual input inefficiencies. Therefore, we conjecture that an overall inefficiency score alone may have limited value for decision making since such a process requires fine-tuning and adjustments of specific input factors of the DMU in order to maximize its overall efficiency. In this paper, the utilization and financial data of a set of hospitals in California is used to empirically test the above conjecture. Our study has several important contributions and practical implications. First, we fine-tune previous efficiency measures on hospitals by refining input and output measures. Second, with variables on organization, management, demographics, and market competition, we identify specific factors associated with a hospitals overall operational inefficiency. More importantly, by decomposing the overall DEA operational inefficiency score into different individual input inefficiencies (including slacks), we further identify specific variables that cause individual input inefficiency. Third, significant differences are observed among factors of the overall inefficiency and individual input inefficiencies. These findings have important implications for identifying congruent factors for performance standard setting and evaluation; it also provides invaluable information for guiding effective resource allocation and better decision making for improving hospital operational efficiency.

Knowledge Life Cycle, Knowledge Inventory, and Knowledge Acquisition Strategies*

For a knowledge and skill centric organization, the process of knowledge management encompasses three important and closely related elements: (i) task assignments, (ii) knowledge acquisition through training, and finally (iii) maintaining proper level of knowledge inventory among the existing workforce. Tradeoff on choices between profit maximization in the short run and agility and flexibility in the long term is a vexing problem in knowledge management. In this study, we examine effects of different training strategies on short-term operational efficiency and long-term workforce flexibility. We address our research objective by developing a computational model for task and training assignment in a dynamic knowledge environment consisting of multiple distinct knowledge dimensions. Overall, we find that organizational slack is an important variable in determining the effectiveness of training strategies. Training strategies focused on the most recent skills are found to be the preferable option in most of the considered scenarios. Interestingly, increased efficiencies in training can actually create preference conflict between employees and the firm. Our findings indicate that firms facing longer knowledge lifecycles, higher slack in workforce capacity and better training efficiencies actually face more difficult challenges in knowledge management.

Involuntary Benchmarking and Quality Improvement: The Effect of Mandated Public Disclosure on Hospitals

This paper documents the responses of Pennsylvania hospitals to the public dissemination by the Pennsylvania Health Care Cost Containment Council (PHC4) in 1990 of mandated hospital disclosures of financial and nonfinancial performance information. We find that PHC4s relative performance disclosures had an effect in that hospitals that performed poorly on patient quality of care, as measured by mortality outcomes, reacted by making significant improvements in this measure by 1992, although this was accompanied by lower reductions in length of stay. Further, we find that the improvements in mortality outcomes were more marked for DRGs in more competitive environments and for hospitals that ranked higher on financial condition in the year of disclosure. Additionally, the rationale for these costly quality improvements in the period following the disclosure appears to be related to market share, that is, poorly performing hospitals lost, whereas better performing hospitals gained in market share.

Availability-adjusted X-factor

The notion of extended X-factor contribution has been proposed and evaluated recently as a tool to identify system capacity constraints based on machine group utilization and raw processing time. This provides a great convenience for factory-floor managers examining system capacity issues by using only local- or machine-level information. The purpose of this study is twofold: to study fundamental properties of the extended X-factor contribution measure augmented with availability, and to use this new measure to investigate resource allocation for optimizing mean cycle time. The availability-adjusted X-factor was first introduced in the context of local cycle time and its relation to allocation of personnel in individual machine groups. The availability-adjusted X-factor contribution measure developed and evaluated in the current study differs from the previous measure by its ability to identify capacity-constraining machines in the entire system. The measure presented herein is a more accurate indicator of capacity constraints than the extended X-factor contribution measures. With an objective to minimize cycle time or maximize throughput by properly allocating available resources, the results presented herein clearly demonstrate the effectiveness of this new measure to identify capacity-constraining machines. This study also uses availability as a decision variable for mean cycle time optimization.

A systematic study of the extended X-factor in relation to effective system capacity

Abstract More and more productivity is demanded from semiconductor manufacturing lines, thus applying more pressure on the “throughput vs. cycle time” constraint. Cycle time and throughput are traditionally used as independent fine-performance measures. A new school of extended X-factor theory has recently emerged. Proponents of this X-factor contribution measure contend that such a metric, which explicitly takes into account utilization and raw processing time of each machine group, is effective for identifying system capacity constraints. This paper systematically studies the dynamics of a complex semiconductor line to reveal the relationship between the extended X-factor metric and the effective capacity of the line. This paper also studies the sensitivity of the extended X-factor metric to raw processing time and throughput rate to determine quantitatively its robustness and effectiveness when used to evaluate line performance. The analysis shows that the X-factor contribution measure correctly identifies capacity constraining machine groups and is more effective than utilization for identifying these machine groups when the difference in X-factor contribution is significant among the constraining machine groups. Additional capacity at the high X-factor contribution machine group lowered cycle time beyond adding capacity to the highly utilized machine group in a full-scale model. This study provides important insight on when the extended X-factor measure is more indicative of a system capacity constraint, as compared to a utilization measure.

Contractual Features of Performance-Vested Executive Equity Compensation

This paper investigates the relations between the key contractual features of performance-vested (p-v) executive equity compensation. We hypothesize that contractual features such as relative performance evaluation (RPE) and long performance horizons can be used to filter noise out of market-based performance metrics. In the empirical analysis, we first report that firms with less volatile returns, better stock performance, and more complex businesses are more likely to use market metrics than accounting metrics. The main analyses show that consistent with our hypotheses, firms using market metrics are more likely to adopt RPE and long performance horizons than firms using accounting metrics. Moreover, we find that RPE, the performance horizon, and the number of metrics are interdependent. These findings reveal intricate relations between the contractual features and have implications for the evolving practice of executive equity compensation.