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Prior research has used computer-generated data to illustrate the benefits of the recently developed duration-based costing (DBC) and its affiliate modified duration-based costing (MDBC). The purpose of this paper is to use data from a Fortune 500 corporation to compare its traditional, or functional-based, cost allocation method with that of the recently developed DBC and MDBC models.

A Fortune 500 company provided one month of production data for a particular, key machine within its manufacturing process. The data were used to apply DBC and MDBC.

Variations arising from differences in the models’ cost allocation reveal the advantages of using time-based cost allocation over the traditional, mostly non-time-based allocation to estimate profit.

By using actual data, this case study enhances prior theoretical research concerning the benefits of utilizing DBC and MDBC over the traditional costing method.

This case study is of benefit to practitioners who use traditional costing since it will encourage them to explore DBC and/or MDBC that tend to be more accurate in situations where the old adage of “time is money” applies. Implementing DBC and MDBC was not difficult to do for the Fortune 500 company as all of the components to run the models were readily available.

This is the first study to utilize actual company data to illustrate DBC and MDBC, and thus, adding to the literature concerning DBC and MDBC.

The purpose of this paper is to examine the operating characteristics as well as risk and performance measures of all available self-proclaimed socially responsible funds (hereafter SRFs) in the USA over the ten-year (2007–2016) period. The first research question addressed is: Do SRFs perform as well as the average of all mutual funds in their respective categories? The second research question addressed is: Are SRF expense ratios correlated with fund performance?

This study analyzes all socially responsible equity mutual funds, as self-reported to Morningstar. This paper empirically compares operating characteristics and performance measures of SRFs relative to category averages in the US mutual fund industry. Operating characteristics include expense ratios and annual turnover rates. Performance measures include conventional return, risk and risk-adjusted return measures.

Although prior research suggests that socially responsible investing (SRI) indexes and SRI-friendly stocks have favorable returns, this study finds that these self-proclaimed SRFs underperform the average of all mutual funds in matched equity categories. However, this study demonstrates that a simple filter based on expense ratios can identify those SRFs that will enable investors to do quite well while doing good.

The contribution of this paper is twofold. First, the authors report that self-proclaimed SRFs, as a whole, have not generated competitive returns relative to other mutual funds in the same categories over the past ten years. This result contradicts the notion that socially responsible investors do not give up return performance when investing with their conscience. Second, the authors find that those SRFs with expense ratios in the lowest quartile of their respective category have significantly higher risk-adjusted returns and significantly lower turnover than category averages. Thus, by focusing on SRFs with low-expense ratios, socially responsible investors can do quite well while doing good.

Firms are able to reduce financing costs and/or increase the funds available for expansion by minimizing the amount of funds tied up in current assets. We provide insights into the performance of surveyed firms across key components of working capital management by using the CFO magazine’s annual Working Capital Management Survey. We discover that significant differences exist between industries in working capital measures across time. In addition, we discover that these measures for working capital change significantly within industries across time.

The purpose of this paper is to examine the contemporaneous relationship between changes in corporate reputations and stock prices.

The Harris Interactive Reputation Quotient^TM is used as a measure of corporate reputation. Stock return and risk measures are evaluated for each Reputation Quotient^TM survey period for the years 1999‐2007.

The results provide evidence that, in the aggregate, firm reputations are procyclical. Additionally, firms with improved reputations enjoy lower volatility in their stock prices than firms with diminished reputations.

Due to the Harris Poll Online methodology, it is not clear that the price changes occur concurrently with the change in reputation.

This paper contributes to the finance literature by examining the effect of a change in corporate reputation on stock price.

For a number of reasons ranging from their more recent introduction to their perceived lesser excitement relative to stock-based peers, there have been few studies of fixed income (mainly bond) exchange-traded funds (ETFs). The purpose of this paper is to fill the void by comparing performance measures of fixed income ETFs to fixed income closed-end funds (CEFs).

This paper examines operating characteristics as well as risk and performance measures of all available fixed income ETFs and CEFs in the USA over the last five and ten years ending on December 31, 2014. Operating characteristics include expense ratios, annual turnover rates, tax cost ratios, and tracking error ratios. Performance measures include average annual returns, risks (measured by standard deviations), and risk-adjusted returns (measured by Sharpe ratios and Sortino ratios).

This study finds material and significant difference in a variety of expenses, return measures, and risk measures. Sharpe and Sortino ratio significance is highly dependent on whether net asset values or market values serve as the dependent variable. ETFs would be the preferred choice of fixed income investors who are presumed to be focussing on market-based return measures.

This paper empirically compares operating characteristics as well as risk and performance measures of US fixed income ETFs and fixed income CEFs in the same Morningstar categories over the last five and ten years.

The purpose of this paper is to examine operating characteristics, risk and performance measures of all available vehicles for index investing in US bond funds during the 15‐year period from April, 1994 to March, 2009. The results shed light on the important issue of bond index mutual funds (BIMFs) and bond exchange‐traded funds (BETFs) performance compared with average of all bond mutual funds.

Data were obtained from Morningstar Principia. Operating characteristics include expense ratios, annual turnover rates, and tax cost ratios. Performance measures include average annual returns and return percentile rank in category, risks (measured by standard deviation) and risk‐adjusted returns (measured by the Sharpe ratio).

BIMFs and BETFs have significantly lower expense ratios and annual turnover rates than category averages. Their returns and risk‐adjusted returns are significantly higher than bond category averages.

Future studies will be able to benefit from a larger sample size, longer performance records, and the strength of bond index funds in foreign markets.

Both BIMFs and bond exchange‐traded mutual funds have significantly lower expense and annual turnover rates, making them preferred investment choices.

Efforts by active bond mutual fund managers to beat index benchmarks have largely failed. Investors should be wary of bond mutual fund managers touting their ability to beat the average or a bond index.

The advantage of investment in BIMFs and BETFs is clear.

Despite the extensive research on the determinants and consequences of firm growth, research focusing on how the actual process unfolds is still evolving. An important part of firm growth process research is entrepreneurial cognition. The purpose of this chapter is to explore the relationship between entrepreneurial cognition and firm growth intentions. Specifically, we propose a theoretical model of entrepreneurial cognitive interpretation and categorization of market information as it relates to firm growth intentions. Drawing from the strategic cognition literature in general and strategic issue interpretation literature in particular, we propose that entrepreneurs’ interpretation of market information as opportunity or threat, gain or loss, and controllable or uncontrollable influences their firm growth intentions. Furthermore, our theoretical model discusses the condition under which favorable interpretation of market information leads to higher growth intentions by incorporating insights from the Entrepreneurial Orientation (EO) construct. This chapter extends our understanding of firm growth processes by highlighting the important role cognitive interpretation and categorization play in facilitating or hindering entrepreneurial firm growth.

Pay, tenure and promotion decisions are frequently based upon inferences regarding the value of faculty research. Meanwhile, departmental, college and university reputations are frequently based on perceptions regarding the quality of research being produced by its faculty. Making correct inferences requires accurate measurement of research quality, which is often based upon the journal through which results are shared. This research expands upon the research found elsewhere through its detailed investigation of leading journals in two business disciplines, including examination of four different citation-based measures and four journal characteristics which are exogenous to the quality of any individual piece of research. The paper aims to discuss this issue.

This study assists in the development of an accurate perspective regarding research quality, by studying the popular Journal Citation Reports (JCR) impact factor. A further expansion on the past literature is consideration of three newer journal quality metrics: SCImago Journal Rank (SJR), Source Normalized Impact per Paper (SNIP) and percentage of articles cited. Top-tier journals in finance and information systems are compared to evaluate the consistency of these measures across disciplines. Differences in journal characteristics and their impact on citation-rate based measures of quality are also examined. The potential impact of discipline-based variation in acceptance rate, issue frequency, the time since journal inception and total reviewers are put forth as additional potential exogenous factors that may impact the perception of journal quality. t-Tests are employed for discipline comparisons, while correlation and multiple regression are used for journal characteristic analysis.

There is a significant difference in the JCR impact measures of high-quality finance journals vs high-quality information systems journals, which are correlated with a variety of journal-specific factors including the journal’s acceptance rate and frequency of issue. Information systems journals domination of finance journals persists whether one considers mean, median, minimum or maximum impact factors. SJR measures for finance journals are consistently higher than information systems journals, though the SJR value of any individual journal can be quite volatile. By comparison, the SNIP metric rates premier information systems journals higher. Over 12 percent more of the articles in leading information systems journals are cited during the initial three years.

Logical extensions of this research include examining journals in other business disciplines. One could also evaluate quality measures reaction to variation in journal characteristics (i.e. changes in acceptance rates). Furthermore, one could include other measures of journal quality, including the recently released CiteScore metric. Such research will build on the present research and improve the accuracy of research quality assessment.

To the extent that citation-based research measures and journal-specific factors vary across disciplines as demonstrated by our investigation, discipline-specific traits should be considered adjusted for, when making inferences about the long-term value of recently published research. For instance, finance faculty publishing in journals with JCR readings of 2.0 are in journals that are 53 percent above the discipline’s average, while information systems faculty publishing in journals with JCR readings of 2.0 are in journals that are 18 percent below the discipline’s average. Furthermore, discipline-specific differences in journal characteristics, leading to differences in citation-based quality measures, should be considered when making inferences about the long-term value of recently published research in the process of making recommendations regarding salary adjustments, retention and promotion.

Quantity and quality of research are two hallmarks of leading research institutions. Assessing research quality is very problematic because its definition has changed from being based on review process (i.e. blind refereed), to acceptance rates, to impact factors. Furthermore, the impact factor construct has been a lightning rod of controversy as researchers, administrators and journals themselves argue over which metric to employ. This research is attempting to assess how impact factors and journal characteristics may influence the impact factors, and how these interactions vary business discipline. The research is especially important and relevant to the authors which separately chair departments including finance and information systems faculty, and therefore are in roles requiring assessment of faculty research productivity including quality.

This study is a detailed analysis of bibliographic aspects of the top-tier journals in two quantitative business areas. In addition to the popular JCR, SJR and SNIP measures of performance, the analysis studies the seldom-examined percentage of the article cited metric. A deeper understanding of citation-based measures is obtained though the evaluation of changes in how journals have been rated on these metrics over time. The research shows that there are discipline-related systematic differences in both citation-based research measures and journal-specific factors and that these discipline-specific traits should be considered when making inferences about the long-term value of recently published research. Furthermore, discipline-specific difference in journal characteristics, leading to differences in citation-based quality measures, should be considered when making personnel and remuneration decisions.