On the relationship between inventory and financial performance in manufacturing companies Vedran Capkun HEC Paris, Paris, France

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1 The curren issue and full ex archive of his journal is available a On he relaionship beween invenory and financial performance in manufacuring companies Vedran Capkun HEC Paris, Paris, France Ari-Pekka Hameri Ecole des HEC, Universiy of Lausanne, Lausanne, Swizerland, and Lawrence A. Weiss The Flecher School a Tufs Universiy, Medford, Massachuses, USA Invenory and financial performance 789 Received 3 July 2007 Revised 25 June 2008, 23 December 2008, 3 February 2009 Acceped 10 February 2009 Absrac Purpose The purpose of his paper is o sudy he relaionship beween invenory performance, boh oal invenory (INV) and is discree componens (raw maerial (RMI), work-in-process (WIP), and finished goods (FGI)), and financial performance in manufacuring companies. Design/mehodology/approach Saisical analysis is applied o he financial informaion of US-based manufacuring firms over he 26-year period from 1980 o Findings The paper finds a significan posiive correlaion beween invenory performance (oal as well as he discree componens of invenory) and measures of financial performance (a boh he gross and operaing levels) for firms in manufacuring indusries. The correlaion beween he performance of discree ypes of invenory and financial performance varies significanly across invenory ypes. RMI performance has he highes correlaion wih all financial performance measures. Beween WIP invenory and FGI performance, he former is more highly correlaed wih gross profi measures while he laer is more highly correlaed wih operaing profi measures. Originaliy/value This paper is he firs o sysemaically analyze he relaionship beween invenory performance and financial performance for a large sample of firms across all manufacuring indusries. The paper adds o prior lieraure by discussing and esing he relaionship beween boh INV performance and he discree ypes of invenory (RMI, WIP, and FGI) and profiabiliy of operaions, boh a he gross and a he operaing profi levels. The paper also analyzes he resuls for firms across as well as wihin manufacuring indusries. The resuls obained suppor he operaions managemen lieraure s claim ha a managerial focus on invenory performance resuls in value creaion for manufacuring firms. Keywords Financial performance, Invenory, Process efficiency, Manufacuring indusries Paper ype Research paper The auhors are exremely graeful o he anonymous referees and he ediors for heir commens, suggesions and suppor. The auhors would also like o hank Shannon Anderson, Erkko Auio, Hong Chen, Allan Eberhar, Dan Muzyka, Mo Onsi, Prem Jain, and Suzanne de-treveille. The paper also benefied from workshop paricipans a he European Accouning Associaion Conference, in Dublin, Ireland, and a he American Accouning Associaion Conference in Washingon DC, USA. Inernaional Journal of Operaions & Producion Managemen Vol. 29 No. 8, 2009 pp q Emerald Group Publishing Limied DOI /

2 IJOPM 29, Inroducion The dominan heme of he operaions managemen lieraure over he pas cenury has been o improve operaional performance. This can be achieved by reducing he lead ime from raw maerials o finished goods (faser cycle imes), reducing he amoun of wase in he process (managing he inpu and oupu qualiy), and by reducing he quaniy of physical unis held by he firm (working wih suppliers and cusomers). Numerous echniques have been proposed o achieve his goal, including: business process reengineering, oal qualiy managemen, supply chain inegraion, jus-in-ime (JIT), lean hinking, agile manufacuring, and aciviy-based managemen. The inheren logic of hese echniques is self eviden and widely acceped. The majoriy of success sories in operaions managemen sem from small sample research in he auomoive, machinery, and job-shop (assembly) indusries. These sudies documen increased marke share, higher profiabiliy and greaer produc qualiy for firms ha have employed he above echniques o improve heir operaions. This paper aims o exend he evidence on he effecs of improving invenory performance wih a large sample sudy, an examinaion of oal as well as he discree componens of invenory, in addiion o an examinaion boh across all manufacuring firms and wihin manufacuring indusries. We analyze he relaionship beween raw maerials (RMI), work-in-process (WIP), finished goods (FGI), and oal invenory (INV) performance (invenory performance) o he profiabiliy of operaing aciviies (financial performance) of US manufacuring firms in he period. For he purpose of his sudy we use invenory levels scaled by sales as a measure of invenory performance. We find ha improving a firm s invenory performance (lowering he invenory o sales raio) yields beer financial performance measured boh a he gross profi and a he operaing profi levels. Decomposing INV ino is componen pars (RMI, WIP, and FGI) reveals ha he correlaion is driven by all hree discree invenory ypes. The size of he correlaion, however, varies significanly across invenory ypes and across financial performance measures. These resuls are consisen wih and exend hose of prior research, in paricular ha of Chen e al. (2005) and Shah and Shin (2007). We furher analyze he changes in invenory performance and financial performance over ime (from 1980 hrough 2005) and find a decrease in INV levels scaled by sales (increase in invenory performance), consisen wih Rajagopalan and Malhora (2001) and Chen e al. (2005). However, he decomposiion of INV ino is componen pars reveals ha he main componen of he decrease in INV is he reducion of he WIP invenory. This suggess ha manufacuring firms effors o improve heir producion invenory performance is focused on WIP invenory. The change in financial performance measures was mixed over he sample period. Regardless of he rend in eiher invenory performance or financial performance measures, he correlaion beween invenory performance and financial performance remains presen across all invenory ypes and financial performance measures. This sudy expands our knowledge of he relaionship beween firm level invenory and financial performance, which as noed by Shah and Shin (2007) is no sraigh forward in he lieraure. Firs, prior research examining his relaionship has been limied o small sample sudies concenraed in a few manufacuring indusries. By conras, our paper uses a large sample of firms across all manufacuring indusries. Second, due o he differenial impac invenory performance migh have on producion

3 and operaing coss, we measure financial performance a boh he gross and operaing profi levels. Third, we incorporae he possibiliy raised by prior research ha he sources, coss and benefis of invenory improvemens could be very differen (Balakrishnan e al., 1996; Lieberman e al., 1999; Lieberman and Demeeser, 1999) by analyzing he invenory performance of he discree componens of invenory (RMI, WIP, and FGI), and heir correlaion wih financial performance. To our knowledge, his is he firs sudy o empirically es hese relaionships. In addiion o our main conribuions noed above, we also analyze he cross-secional and longiudinal correlaions beween invenory performance and financial performance, use a large sample of manufacuring firms and firm-level daa over a longer ime period[1], and offer an explanaion for why beer invenory performance should lead o beer financial performance and increased firm valuaion. We proceed by presening he relevan lieraure on he relaionship beween invenory performance and financial performance, as well as he relaed research on how operaional mehodologies have affeced manufacuring firms since heir inroducion in he early 1980s. This discussion is followed by a descripion of he research quesions, sample descripion, and applied mehodologies. We conclude wih a presenaion of our key findings wih heir managerial implicaions. Invenory and financial performance Lieraure review Abou half a cenury ago, Forreser s (1961) non-linear simulaions on informaion and delivery delays in inernal operaions and supply chains helped academics and managers undersand how informaion disorion and order baching lead o ever longer lead imes and invenory build-up. Scale and cos-cenric manufacuring dominaed operaions managemen unil he 1970s when he qualiy movemen urned he focus o coninuous improvemen and errorless operaions. JIT, and is emphasis on reducing wase, invenory reducion, and operaional flexibiliy hrough a pull sysem, appeared in he early 1980s. Goldra and Cox (1984) and Suri (1998) argued for a relenless reducion of bolenecks and lead ime. These approaches (ha is, heory of consrains and quick response manufacuring) were based on flow and lead-ime reducion and presened cases from job shops and machine assembly companies o suppor heir claims. Oher scholars and praciioners conveyed similar messages under differen labels such as ime-based compeiion (Salk, 1988) and lean manufacuring (Womack e al., 1990). Lead ime reducion is ofen described in he operaions managemen lieraure as arising from iniiaives such as JIT/lean producion or agiliy (Naylor e al., 1999; Barezzaghi e al., 1995) raher han from idenifying and reducing congesion a bolenecks, reducing lo sizes, and moving o a produc layou from a funcional one. Kouferos e al. (1998) claim ime-based manufacuring is relaed o shop-floor employee involvemen, seup ime reducion, cellular manufacuring, qualiy improvemen effors, prevenive mainenance, dependable suppliers, and pull producion, bu do no relae hese consrucs o he principles ha drive lead ime. According o Schmenner (2001), companies ha focus on flow wih an emphasis on operaional speed and variabiliy reducion ouperform companies emphasizing oher goals. This conclusion is consisen wih he principles of operaions managemen, based on queuing heory, which demonsraes he relaionships beween lo sizes, cycle imes, bolenecks, lead imes, and process variabiliy (Hopp and Spearman, 2001; Schmenner and Swink, 1998).

4 IJOPM 29,8 792 Recen research on he relaionship beween a managerial focus on improving operaions and performance has been concenraed primarily on JIT. Virually all of his research has been carried ou a he plan level, is case oriened wih a small sample size, or is a narrow indusry specific survey. The overwhelming majoriy of sudies show he posiive effec of JIT implemenaion on earnings and financial performance hrough he increase in produciviy and invenory efficiency (Neil and O Hara, 1987; Huson and Nanda, 1995; Lawrence and Hoensein, 1995; Boyer, 1996; Fulleron e al., 2003; Nahm e al., 2003; Chrisensen e al., 2005). Oher sudies like Callen e al. (2000) and Fulleron and McWaers (2001) provide suppor ha JIT implemenaion improves firm performance hrough lower invenory levels, reduced qualiy coss, and greaer cusomer responsiveness wih higher profis. Wih only wo excepions (Balakrishnan e al., 1996; Sakakibara e al., 1997), hese sudies all conend ha sraegies aimed a increasing invenory performance (primarily hrough reduced invenory levels) are posiively relaed o increases in value added defined as an increase in marke share, sales, and profiabiliy. The lead ime relaed research has focused principally on he auomoive, machinery, and compuer assembly operaions. By conras, supply chain research exends o all indusries. The underlying emphasis in supply chain managemen is on informaion ransparency, reliable lead imes, and he clever posiioning of various value-adding operaions in long logisical chains. Hendricks and Singhal (2003) documen ha supply chain glich announcemens are associaed wih negaive abnormal sock reurns, observing ha he impac is greaer for smaller firms. To dae, he direc relaionship beween invenory performance and financial performance has been invesigaed only o a very limied exen. Claycomb e al. (1999) provide a model of he causal relaionship beween invenory and financial performance. Gaur e al. (2005) and Roumiansev and Neessine (2007) boh documen a negaive correlaion beween invenory performance and financial performance in he reail indusry whose value proposiion relaes o efficien produc availabiliy. By conras, he value proposiion of he manufacuring indusry is based primarily on value adding operaions, produc innovaion and efficien order fulfillmen. Chen e al. (2005) analyze he link beween INV and long-erm sock reurns of manufacuring firms. They find ha while firms wih abnormally high invenory levels have poor long-erm sock reurns, firms wih slighly lower han average invenory ouperform firms wih exremely low INV. Shah and Shin (2007) use aggregae secor daa o show a link beween invenory and profiabiliy for he wholesale, reail, and manufacuring secors. However, none of he above sudies analyze he relaionship beween invenory performance and financial performance of manufacuring indusries a he firm level, nor do hey analyze he relaionship beween differen financial performance measures wih invenory performance. No sudy o dae has examined he relaionship beween he invenory performance of he discree componens of invenory wih financial performance. Our paper aemps o fill his gap. The use of differen measures of financial performance allows he analysis of boh he level of profi above producion coss (gross profi) as well as afer operaing expenses (operaing profi). Including he performance of he discree invenory componens allows a es for any differenial impacs on he coss of producion and operaing expenses (Palepu e al., 2007, pp , for an overview of financial performance measures).

5 Our paper is he firs o look a he discree componens of invenory (RMI, WIP, and FGI) and heir correlaion wih financial performance and we do his boh a he firm level as well as for firms wihin specific indusries. We build on prior research suggesing ha sources of reducion, coss of reducion and benefis arising from he reducion in RMI, WIP, and FGI are very differen. Hopp and Spearman (2001) indicae ha RMI is deermined by discouns, economies of scale, qualiy problems, changes in demand and supply, and obsolescence. WIP is deermined by queuing, processing, waiing for bach, moving, and waiing o mach. Finally, FGI is deermined by cusomer responsiveness, bach producion, forecas errors, producion variabiliy, and seasonaliy. For a descripion of differences beween discree invenory componens (Krajewski and Rizman, 2005; Heizer and Render, 2006). Lieberman e al. (1999) empirically analyze he sources of change in invenory of RMI, WIP, and FGI in he auomoive indusry. They find ha all hree discree ypes of invenory depend on managerial acions, bu in differen ways. While formal mehods o reduce invenory (like JIT) reduce WIP and FGI, hey have no impac on he RMI. They also find ha mainaining communicaion wih suppliers and cusomers leads o reducions in RMI and FGI, wih no impac on WIP invenory. The coss and benefis associaed wih he change may differ beween invenory ypes since he sources of hese changes are differen. As Balakrishnan e al. (1996, p. 195) argue, reducing WIP invenory requires less coordinaion wih a firm s suppliers or cusomers han is required o reduce RMI or FGI and hus imposes fewer implemenaion coss. Balakrishnan e al. (1996) furher argue ha unlike reducions in RMI, reducing he WIP invenory does no require sabiliy of he supply chain and ha WIP holds he highes poenial for improvemen by reducing producion lead ime, reducing conversion coss and increasing manufacuring flexibiliy. Several sudies show ha implemenaion of JIT has a differenial impac on discree invenory ypes, wih he reducion of WIP invenory presen in all sudies, bu resuls for RMI and FGI remain mixed (Baron e al., 1988; Norris e al., 1994). Lieberman and Demeeser (1999) sugges ha a reducion in invenory (primarily WIP) increases produciviy. Overall, prior research suggess ha he coss associaed wih improving invenory performance are differen across RMI, WIP, and FGI. Prior research also suggess ha RMI and FGI will depend on supply managemen and he relaionship wih cusomers and ha heir main impac on performance comes from carrying coss. By conras, WIP invenory depends on changes in producion speed while is impac on financial performance comes from manufacuring flexibiliy, increased producion aciviy and lower coss of producion. Recen research has begun o analyze he changes in he naure and level of invenory over ime. Rajagopalan and Malhora (2001) use aggregae indusry daa provided by he Census Bureau and find mixed resuls on he rends in INV and is componens. By conras, Chen e al. (2005) use firm-level RMI, WIP, and FGI daa from he Compusa daabase and documen a 16 per cen drop (from 96 o 81 days) in he average INV level (days of invenory) of all publicly-raded US manufacuring firms over he 20-year period from 1982 o Gaur e al. (2005) provide evidence of a reducion in invenory in he reail secor. Our resuls confirm he above findings and reveal ha he improvemen in INV over he period comes primarily from improvemens in WIP invenory performance and o a lesser exen RMI performance wih no change in he FGI performance. Invenory and financial performance 793

6 IJOPM 29, Research quesions, sample selecion, and mehodology The operaions managemen lieraure indicaes financial performance should be a leas parially explained by invenory performance. Following he lieraure review we se our hypoheses as: H1a. A firm s invenory performance will be posiively correlaed wih he firm s financial performance. H1b. The correlaion beween a firm s invenory performance and financial performance will be presen across manufacuring indusries. H2a. The performance of all hree discree componens of a firm s invenory (RMI, WIP, and FGI) will be posiively correlaed wih he firm s financial performance. H2b. The correlaion beween he performance of all hree discree componens of a firm s invenory and he firm s financial performance will be presen across manufacuring indusries. Prior lieraure indicaes ha a firm s sraegic choice can simulaneously impac invenory and financial performance (Keokivi and Schroeder, 2004; Mendelson and Parlakurk, 2008). For example, firms posiioning hemselves o provide heir cusomers wih high service levels may hold greaer levels of invenory (boh in quaniy and variey), resuling in a posiive correlaion beween invenory levels and financial performance. We conrol for his by using changes in (as opposed o levels of) invenory performance and financial performance. By looking a changes over ime, a negaive correlaion beween invenory and financial performance indicaes ha he effec exiss over ime beween firms and wihin he same sraegy. Firms can also change sraegies (ha is, decide o specialize heir produc line hereby reducing he number of producs in heir porfolio and heir overall invenory). To conrol for his possibiliy, we analyze firms improvemens beween wo ime periods and over he enire sample period separaely hereby eliminaing he poenial impac of firms decisions o change heir sraegic choice on our resuls. Invenory performance and financial performance can also be influenced by sales surprises (Gaur e al., 2005). More specifically, if a firm misses (beas) is sales arge i will have a higher (lower) level of invenory and lower (higher) profi han projeced. We conrol for his in wo ways. Firs, we use boh annual and quarerly daa for invenory and financial performance over a 26-year period (for simpliciy we presen only annual daa). The long ime period reduces any poenial impac of a sales surprise in a given year. Second, we analyze he ime rend of boh invenory performance and financial performance. A coninual improvemen is unlikely o resul from a given year s incorrec sales forecas. Addiionally, his effec is ypical of firms in he reail indusry (Gaur e al., 2005), and is unlikely o impac our sample which is resriced o manufacuring firms. The Compusa daabase is used boh o rerieve he Sandardized Indusrial Classificaion (SIC) codes as well as o collec annual and quarerly financial repor daa. The SIC codes are used o resric he sample o manufacuring firms (SIC codes 2000 o 3999) and o separae hem by indusry (Fama and French, 1997, indusry classificaion). To compue he change in our variables (as defined below), we require a leas wo consecuive periods wih financial reporing daa and exclude daa wihou a consecuive period. As proxies for financial performance, we use he following measures:

7 EBITS j; ¼ EBIT j; Sales j; ; GPS j; ¼ Sales j; 2 COGS j; Sales j; where EBIT is earnings before ineress and axes for firm j in year, Sales are oal sales for firm j in year, and COGS is cos of goods sold for firm j in year. Using boh gross profi (GP) and EBIT allows us o analyze he deerminans of financial performance on wo levels. The GP reflecs he added value as a difference beween sales and he cos of producion, while EBIT proxies for he profiabiliy of he business afer deducing all operaing expenses, no only he producion coss. Using eiher earnings before ineress, axes, depreciaion and amorizaion (EBITDA) or ne income afer ax insead of EBIT does no change our resuls qualiaively. When scaled by sales, gross and operaing profis represen gross and operaing margin (profiabiliy of firm s operaions). Our resuls are qualiaively unchanged when we use an alernaive financial performance measure equaling gross and operaing profis scaled by oal asses. These financial performance measures, as opposed o profiabiliy of firm s operaions, represen he reurn on invesed asses (Palepu e al., 2007, pp ). Pas lieraure provides us wih several possible measures of invenory performance which include scaling invenory by cos of goods sold (Huson and Nanda, 1995), by combinaion of maerial coss and value added (Rajagopalan and Malhora, 2001) and by sales (Chen e al., 2005). Using any of hese measure yields qualiaively unchanged resuls. To be consisen wih financial performance measures, we scale invenory by sales: RMIS j; ¼ avgðrmi j;21; RMI j; Þ ; WIPS j; ¼ avgðwip j;21; WIP j; Þ ; Sales j; Sales j; Invenory and financial performance 795 FGIS j; ¼ avgðfgi j;21; FGI j; Þ Sales j; ; INVS j; ¼ avgðinv j;21; INV j; Þ Sales j; where RMIS is he performance of RMI for firm j in year, WIPS is he performance of WIP invenory, FGIS is he performance of FGI, INVS is he performance of INV. Sales are oal sales of firm j for year. Avg is he arihmeic average of invenory levels a he beginning and he end of he year. These invenory performance measures are used hroughou he paper in all ables, resuls and discussions. We derive a model similar o Shah and Shin (2007) o es for he relaionship beween our financial performance and invenory performance measures. The following levels specificaion models are esimaed: X X EBITS j; ¼ a þ b 1 EBITS j;21 þ b 2 Size j; þ b 3 S j; þ Indk þ Yeark þ 1 X X GPS j; ¼ a þ b 1 GPS j;21 þ b 2 Size j; þ b 3 S j; þ Indk þ Yeark þ 1 ð1þ ð2þ EBITS is operaing profi scaled by sales, GPS is he gross profi scaled by sales. Size is he naural log of inflaion adjused oal asses. S is he invenory performance measure for INVS, RMIS, WIPS, or FGIS. Ind is he se of indusry dummy variables and Year is he se of year dummy variables. We furher esimae regression models ha ake ino accoun all hree-invenory ypes as follows:

8 IJOPM 29,8 EBITS j; ¼ a þ b 1 EBITS j;21 þ b 2 Size j; þ b 3 RMIS j; þ b 4 WIPS j; þ b 5 FGIS j; X X þ Indk þ Yeark þ 1 ð3þ 796 GPS j; ¼ a þ b 1 GPS j;21 þ b 2 Size j; þ b 3 RMIS j; þ b 4 WIPS j; þ b 5 FGIS j; X X þ Indk þ Yeark þ 1 We expec all invenory performance measures o have negaive and saisically significan coefficiens. The less invenory a firm requires per uni of sales, he greaer is financial performance (all else equal). We expec his resul o hold across invenory ypes (RMI, WIP, and FGI) and across indusries. We also expec he resul o hold for boh, operaing financial performance (EBIT) and gross financial performance (GP). Finally, we expec posiive and saisically significan coefficiens associaed wih he lagged financial performance variables (auocorrelaion), consisen wih he halo effec. The halo effec is he effec where pas financial performance significanly affecs curren performance (Sine e al., 2003). We conrol for he size effec, bu make no predicions abou he sign or significance of he coefficien, since he size effec depends largely on he indusry, cycle and performance measures used (Chan e al., 1985; Chan and Chen, 1988). Nex, we re-esimae he above regressions using change specificaion models insead of he above levels specificaion. We analyze he impac of he changes in invenory performance measures on changes in financial performance measures using he following regression models: ð4þ X X DEBITS j; ¼ a þ b 1 DEBITS j;21 þ b 2 Size j; b 3 DS j; þ Indk þ Yeark þ 1 X X DGPS j; ¼ a þ b 1 DGPS j;21 þ b 2 Size j; þ b 3 DS j; þ Indk þ Yeark þ 1 DEBITS j; ¼ a þ b 1 DEBITS j;21 þ b 2 Size j; þ b 3 DRMIS j; þ b 4 DWIPS j; X X þ b 5 DFGIS j; þ Indk þ Yeark þ 1 DGPS j; ¼ a þ b 1 DGPS j;21 þ b 2 Size j; þ b 3 DRMIS j; þ b 4 DWIPS j; X X þ b 5 DFGIS j; þ Indk þ Yeark þ 1 ð5þ ð6þ ð7þ ð8þ We expec he changes in invenory performance o be negaively associaed wih he changes in financial performance, across invenory ypes and indusries. In addiion, we expec he coefficien associaed wih he lagged financial performance measures o be negaive and saisically significan indicaing a mean reversion of changes in financial performance. All he above regressions are esimaed using ordinary leas square (OLS), wih year and indusry fixed effecs. As robusness checks, we conrol for firm fixed effecs

9 (using fixed effecs regressions) and random effecs (using random effecs regressions) and also use he Fama-MacBeh regressions (Fama and MacBeh, 1973). All hese alernaive mehods (omied from he presenaion) suppor he resuls of our OLS regressions. 4. Empirical analysis, resuls and discussion To es wheher beer invenory performance is posiively correlaed wih beer financial performance, we creae a sample of US manufacuring firms (wih SIC codes from 2000 o 3999) from he Compusa daabase for he period. We exclude all firm-year observaions wihou daa available on RMI, WIP invenory, or FGI. We also exclude all firm-year observaions wih daa unavailable on sales, cos of goods sold or oal asses. Panel A of Table I shows he descripive saisics for our firm-year sample of all US manufacuring firms, conaining 52,254 observaions. The descripive saisics show all observaions found in he Compusa daabase, winsorized a he 1 percen level, for all firm-year available variables. Panel B of Table I shows median values for he full sample of all US manufacuring firms over he period. Our financial performance measures show a mixed rend wih median EBITS (operaing profi) decreasing, and median GPS (gross profi) increasing over he sample period. Consisen wih prior sudies on changes in invenory performance (Rajagopalan and Malhora, 2001; Chen e al., 2005) we also find an increase in he invenory performance of RMI and WIP invenory. There is no increase in FGI performance. The increase is mos prevalen in WIP invenory where he performance has doubled. We presen our levels specificaion regressions resuls (equaions (1)-(4)) in Table II. As hypohesized, he coefficiens associaed wih all four-invenory performance variables are negaive and saisically significan in all regressions. Our resuls indicae beer invenory performance (a lower invenory-o-sales raio) is posiively associaed wih he profiabiliy of a firm s operaions. Invenory performance is posiively associaed wih financial performance measures a boh he gross and operaing profi levels. The regression esimaes also reveal ha invenory performance is posiively relaed o financial performance regardless of he invenory ype (RMI, WIP, or FGI). Differences in he srengh of he correlaion, however, exis beween discree invenory ypes. The RMI performance exhibis he sronges correlaion wih financial performance across all financial measures. The WIP performance has a sronger correlaion wih gross financial performance, while FGI has a sronger correlaion wih operaing financial performance. The differences beween coefficiens associaed wih RMI, WIP, and FGI performance variables are all saisically significan. The lagged financial performance measure, as expeced, has a high posiive and saisically significan coefficien indicaing a high level of auocorrelaion. Relaxing his assumpion and removing he lagged financial performance measure from he regression does no change our resuls qualiaively. The coefficiens associaed wih all invenory performance variables say saisically significan while he R 2 of he regressions decrease, on average, by half. The size coefficien is posiive and significan across all regression models. The resuls of our changes specificaion regressions (equaions (5)-(8)) are presened in Table III and suppor he levels specificaion models resuls. Firms ha decrease invenory relaive o sales increase boh gross profi and operaing profi, consisen wih our hypoheses. All coefficiens associaed wih our invenory performance measures (DRMIS, DWIPS, DFGIS, and DINVS) are negaive and saisically significan. Invenory and financial performance 797

10 IJOPM 29,8 798 Table I. Descripive saisics Panel A N Mean SD Minimum p25 Median p75 Maximum Toal asses (1980 $ million) 52, , Sales (1980 $ million) 52, , , EBITS 52, % % % 20.90% 6.02% 11.04% 32.42% GPS 52, % 35.45% % 23.71% 34.20% 47.53% 82.15% RMIS 52, % 7.09% 0.07% 3.32% 5.66% 9.27% 45.52% WIPS 52, % 6.01% 0.00% 1.02% 2.94% 6.14% 35.68% FGIS 52, % 6.90% 0.00% 2.70% 5.59% 9.67% 40.18% INVS 52, % 14.47% 2.82% 11.37% 16.62% 23.95% 98.85% Panel B changes in medians over he period Year EBITS (%) GPS (%) RMIS (%) WIPS (%) FGIS (%) INVS (%) N , , , , , , , , , , , , , , , ,336 (coninued)

11 , , , , , , , , , ,966 Noes: Sample of 52,254 firm-year observaions of US manufacuring firms for he period. Daa were colleced from he Compusa daabase. EBITS is earnings before ineress and axes scaled by sales. GPS is he difference beween sales and cos of goods sold scaled by sales. RMIS is he performance of RMI, WIPS is he performance of WIP and FGIS is he performance FGI, all scaled by sales Invenory and financial performance 799 Table I.

12 IJOPM 29,8 800 Table II. Levels specificaion regressions Panel A EBITS Lagged EBITS *** *** *** *** *** (42.012) (42.351) (44.453) (43.747) (41.659) Size *** ** *** *** *** (8.829) (2.207) (16.549) (17.667) (4.213) INVS *** (24.229) RMIS *** *** (22.788) (21.344) WIPS *** *** (12.759) (8.199) FGIS *** *** (17.853) (14.700) Consan *** *** *** ** *** (13.255) (12.094) (4.728) (2.372) (15.051) Indusry conrols Included Included Included Included Included Year conrols Included Included Included Included Included N 52,043 52,043 52,043 52,043 52,043 F Prob. F R Adjused R Panel B GPS Lagged GPS *** *** *** *** *** (40.906) (40.794) (41.798) (42.120) (40.581) Size *** *** *** (5.554) (0.793) (11.944) (12.370) (1.247) INVS *** (14.610) RMIS *** *** (15.118) (14.285) WIPS *** *** (9.862) (6.403) FGIS *** *** (8.430) (4.076) Consan *** *** *** *** *** (19.465) (19.630) (12.450) (14.205) (19.801) Indusry conrols Included Included Included Included Included Year conrols Included Included Included Included Included N 52,046 52,046 52,046 52,046 52,046 F Prob. F R Adjused R Noes: *, **, and *** represen saisically significan coefficiens a he 10, 5 and 1 percen levels, respecively. OLS regression models of financial performance (EBITS and GPS). Sample of 52,254 firm-year observaions of US manufacuring firms for he period. Daa were colleced from he Compusa daabase. EBITS is earnings before ineress and axes scaled by sales. GPS is gross profi (he difference beween sales and cos of goods sold) scaled by sales. INVS is he performance of INV, RMIS is he performance of RMI, WIPS is he performance of WIP invenory and FGIS is he performance of FGI, all scaled by sales

13 Panel A DEBITS Lagged DEBITS *** ** * ** *** (2.701) (2.281) (1.809) (2.151) (2.705) Size *** *** *** *** *** (8.382) (8.425) (7.534) (7.970) (8.631) DINVS *** (42.362) DRMIS *** *** (39.227) (28.126) DWIPS *** *** (27.245) (9.552) DFGIS *** *** (31.383) (15.578) Consan *** * *** *** *** (3.204) (1.694) (3.385) (4.075) (2.712) Indusry conrols Included Included Included Included Included Year conrols Included Included Included Included Included N 45,657 45,657 45,657 45,657 45,657 F Prob. F R Adjused R Panel B DGPS Lagged DGPS *** *** *** *** *** (3.808) (4.119) (3.762) (3.803) (3.971) Size *** *** *** *** *** (4.734) (4.838) (4.652) (4.812) (4.897) DINVS *** (26.924) DRMIS *** *** (25.847) (18.780) DWIPS *** *** (18.969) (7.140) DFGIS *** *** (20.146) (7.712) Consan *** *** *** *** *** (3.472) (2.676) (3.659) (4.008) (3.145) Indusry conrols Included Included Included Included Included Year conrols Included Included Included Included Included N 45,659 45,659 45,659 45,659 45,659 F Prob. F R Adjused R Noes: *, **, and *** represen saisically significan coefficiens a he 10, 5, and 1 percen levels, respecively. OLS regression models of changes in financial performance (EBITS and GPS). Sample of 52,254 firm-year observaions of US manufacuring firms for he period. Daa were colleced from he Compusa daabase. EBITS is earnings before ineress and axes scaled by sales. GPS is gross profi (he difference beween sales and cos of goods sold) scaled by sales. INVS is he performance of INV, RMIS is he performance of RMI, WIPS is he performance of WIP invenory and FGIS is he performance of FGI, all scaled by sales Invenory and financial performance 801 Table III. Changes specificaion regressions

14 IJOPM 29,8 802 Consisen wih our levels specificaion regressions, he change in RMI performance has he highes coefficien indicaing he highes associaion wih he change in financial performance across all models. The change in WIP invenory performance has a sronger correlaion wih he change in gross financial performance measures han he change in FGI performance. This relaionship reverses in he operaing financial performance regression models. All differences in coefficiens are saisically significan. The coefficien associaed wih he lag change in financial performance is negaive and saisically significan indicaing a mean reversion for gross profi scaled by sales. However, he coefficien is posiive and saisically significan for operaing profi scaled by sales[2]. The coefficien associaed wih he size variable is negaive and saisically significan across all regression models. Finally, we separaely analyze he manufacuring indusries using he regression model from equaion (1). Table IV shows hese resuls for he EBITS financial performance measure. The relaionship beween invenory (RMI, WIP, and FGI) performance and financial performance is presen in mos indusries. The lower he invenory per sales dollar, he greaer he operaing profi. This relaionship holds in un-abulaed resuls for mos indusries using any of he regression models discussed in his sudy. The impac of differen ypes of invenory (RMI, WIP, or FGI) on operaing profi varies significanly and predicably beween indusries. In assembly indusries, like auomobiles, machinery, and compuers, he reducion of all invenories improves operaing profi. As our prior analysis shows, he reducion in WIP drives he reducion in FGI, which in urn allows firms o be more reacive. This is especially rue for indusries producing shor life-cycle producs like elecronic equipmen, in which componens, producion faciliies and producs end o have ever shorer life-spans. This also applies, o a lesser exen, in high-ech indusries like medical equipmen and insrumens. By conras, he above resul is no as eviden in basic commodiies and process indusries where relaively cheap RMI and WIP will no play as imporan a role on operaing profi. However, a producion process which saisfies demand efficienly wih a low FGI does have a srong impac on operaing profis. This also applies o exiles and oher fashion indusries where producs, once in he marke, need o be consumed rapidly before hey lose heir araciveness. 5. Conclusion We analyze he relaionship beween invenory performance, boh INV and is discree componens (RMI, WIP, and FGI), and financial performance using a large sample sudy of US-based manufacuring firms over he 26-year period from 1980 o Our resuls show a srong correlaion beween invenory performance and financial performance across a broad array of manufacuring indusries. Performance of oal as well as all hree discree componens of invenory is posiively associaed wih financial performance. However, he srengh of he correlaion differs beween invenory ypes. FGI performance has he sronges correlaion wih financial performance. Beween WIP and FGI performance, WIP invenory performance has a sronger correlaion wih he GP measures of financial performance, while finished good invenory performance has a sronger correlaion wih operaing profi measures of financial performance. Our resuls suppor he operaions managemen lieraure s claim ha a managerial focus on operaions performance in paricular increases in invenory performance correlaes wih significan value creaion.

15 Lagged EBITS Size WIPS RMIS FGIS Consan N Food producs *** *** *** *** *** 1722 Candy and soda *** *** *** *** *** *** 307 Beer and liquor *** *** *** 418 Tobacco producs *** *** ** * ** 132 Recreaion *** * *** *** *** *** 996 Prining and publishing *** *** *** ** *** ** 764 Consumer goods *** ** *** *** *** *** 2316 Apparel *** *** *** * *** *** 1848 Medical equipmen *** *** *** *** *** 3907 Pharmaceuical producs *** *** *** *** *** 3014 Chemicals *** *** *** *** ** *** 2036 Rubber and plasic producs *** *** *** *** *** 1629 Texiles *** *** *** *** *** *** 1125 Consrucion maerials *** * *** *** *** 2871 Seel works *** *** *** *** ** 1708 Fabricaed producs *** *** *** ** Machinery *** *** *** *** *** *** 4384 Elecrical equipmen *** *** *** *** *** 2337 Auomobiles and rucks *** *** * *** *** Aircraf *** *** Shipbuilding, railroad equipmen *** *** * Defense *** *** *** 128 Compuers *** *** *** *** *** 4060 Elecronic equipmen *** *** *** *** *** 7513 Measuring and conrol equipmen *** *** *** *** *** 3366 Business supplies *** * *** *** *** *** 1660 Shipping conainers *** *** *** *** 366 Noes: *, **, and *** represen saisically significan coefficiens a he 10, 5, and 1 percen levels, respecively. OLS regression models of financial performance (EBITS) per Fama and French (1997) indusry classificaion. Sample of 52,254 firm-year observaions of US manufacuring firms for he period. Daa were colleced from he Compusa daabase. EBITS is earnings before ineress and axes scaled by sales. RMIS is he performance of RMI, WIPS is he performance of WIP invenory and FGIS is he performance of FGI, all scaled by sales. N is he number of observaions Invenory and financial performance 803 Table IV. Indusry analysis

16 IJOPM 29,8 804 Our resuls are based on correlaions and do no prove causaliy beween our variables. Furhermore, his paper is limied o daa available in public daabases and includes only publicly lised manufacuring US firms over he sample period. While our sample consiss of a large number of firms ha are represenaive of he US economy, he conclusions of his paper should no be generalized beyond is scope. The colleced daa are for he firm as a single eniy, and do no accoun for he complexiy of firms ha operae in more han one manufacuring faciliy. The daa used in his paper are repored by firms and as such are a resul of reporing incenives and accouning choices made, which make hem noisy compared o case sudies and surveys. Financial performance and invenory performance measures and resuling findings used in his paper should be inerpreed accordingly. However, prior lieraure has documened many posiive urnarounds in manufacuring companies hrough he reducion of invenories and faser operaions. Our saisical analysis furher suppors he hypohesis of a causal relaionship beween invenory performance and financial performance. For everyday managers of manufacuring companies, he underlying message of his paper is direcly linked wih boh he shor- and long-erm performance of heir enerprise. The saisical analysis indicaes ha in mos indusries invenory performance may be a decisive sraegic facor where firms which do no focus on invenory performance underperform heir compeiors. While our resuls show a posiive correlaion beween all he invenory componens and improved financial performance, managers should probably focus heir effors on reducing RMI where he relaionship is he sronges. When seing up developmen projecs in manufacuring firms, supplier relaionships and parnering appear o be imporan issues along wih he organizaion of he value adding operaions inside he company. This, naurally, does no play down he imporance of accessing reliable and real ime marke informaion. Noes 1. Compared o previous sudies using aggregae secor daa (Rajagopalan and Malhora, 2001; Shah and Shin, 2007). 2. Winsorizing his variable a 2 percen insead of 1 percen would yield he opposie (negaive) sign and a saisically significan coefficien. References Balakrishnan, R., Linsmeier, T.J. and Venkaachalam, M. (1996), Financial benefis from JIT adopion: effecs of cusomer concenraion and cos srucure, The Accouning Review, Vol. 71 No. 2, pp Barezzaghi, E., Spina, G. and Vergani, R. (1995), Lead-ime models of business processes, Inernaional Journal of Operaions & Producion Managemen, Vol. 14 No. 5, pp Baron, F.M., Agarwal, S.P. and Rockwell, L.M. (1988), Meeing he challenge of Japanese managemen conceps, Managemen Accouning, Vol. 74, pp Boyer, K. (1996), An assessmen of managerial commimen o lean producion, Inernaional Journal of Operaions & Producion Managemen, Vol. 16 No. 9, pp Callen, J.L., Fader, C. and Krinsky, I. (2000), Jus-in-ime: a cross-secional plan analysis, Inernaional Journal of Producion Economics, Vol. 63 No. 3, pp Chan, K. and Chen, N. (1988), An uncondiional asse-pricing es and he role of firm size as an insrumenal variable for risk, Journal of Finance, Vol. 43 No. 2, pp

17 Chan, K., Chen, N. and Hsieh, D. (1985), An exploraory invesigaion of he firm size effec, Journal of Financial Economics, Vol. 14 No. 3, pp Chen, H., Frank, M.Z. and Wu, O.Q. (2005), Wha acually happened o he invenories of American companies beween 1981 and 2000?, Managemen Science, Vol. 51 No. 7, pp Chrisensen, W.J., Germain, R. and Birou, L. (2005), Build-o-order and jus-in-ime as predicors of applied supply chain knowledge and marke performance, Journal of Operaions Managemen, Vol. 23 No. 5, pp Claycomb, C., Germain, R. and Droge, C. (1999), Toal sysem JIT oucomes: invenory, organizaion and financial effecs, Inernaional Journal of Physical Disribuion & Logisics, Vol. 29 No. 10, pp Fama, E.F. and French, K.R. (1997), Indusry cos of equiy, Journal of Financial Economics, Vol. 43 No. 2, pp Fama, E.F. and MacBeh, J.D. (1973), Risk, reurn and equilibrium: empirical ess, Journal of Poliical Economy, Vol. 81 No. 3, pp Forreser, J. (1961), Indusrial Dynamics, MIT Press, New York, NY. Fulleron, R.R. and McWaers, C.S. (2001), The producion performance benefis from JIT implemenaion, Journal of Operaions Managemen, Vol. 19 No. 1, pp Fulleron, R.R., McWaers, C.S. and Fawson, C. (2003), An examinaion of he relaionships beween JIT and financial performance, Journal of Operaions Managemen, Vol. 21 No. 4, pp Gaur, V., Fisher, M.L. and Raman, A. (2005), An economeric analysis of invenory urnover performance in reail services, Managemen Science, Vol. 51 No. 2, pp Goldra, E.M. and Cox, J. (1984), The Goal, Norh River Press, New York, NY. Heizer, J. and Render, B. (2006), Operaions Managemen, 8h ed., Prenice-Hall, Chicago, IL. Hendricks, K.B. and Singhal, V.R. (2003), The effec of supply chain gliches on shareholder wealh, Journal of Operaions Managemen, Vol. 21 No. 5, pp Hopp, W.J. and Spearman, M.L. (2001), Facory Physics, 2nd ed., McGraw-Hill, New York, NY. Huson, M. and Nanda, D. (1995), The impac of jus-in-ime manufacuring on firm performance in he US, Journal of Operaions Managemen, Vol. 12 Nos 3/4, pp Keokivi, M. and Schroeder, R. (2004), Manufacuring pracices, sraegic fi and performance: a rouine-based view, Inernaional Journal of Operaions & Producion Managemen, Vol. 24 Nos 1/2, pp Kouferos, X.A., Vonderembse, M.A. and Doll, W.J. (1998), Developing measures of ime-based manufacuring, Journal of Operaions Managemen, Vol. 16 No. 1, pp Krajewski, L.J. and Rizman, L.P. (2005), Operaions Managemen, 7h ed., Prenice-Hall, Chicago, IL. Lawrence, J.J. and Hoensein, M.P. (1995), The relaionship beween JIT manufacuring and performance in Mexican plans affiliaed US companies, Journal of Operaions Managemen, Vol. 13 No. 1, pp Lieberman, M.B. and Demeeser, L. (1999), Invenory reducion and produciviy growh: linkages in he Japanese auomoive indusry, Managemen Science, Vol. 45 No. 4, pp Lieberman, M.B., Helper, S. and Demeeser, L. (1999), The empirical deerminans of invenory levels in high-volume manufacuring, Producion and Operaions Managemen, Vol. 8 No. 1, pp Mendelson, H. and Parlakurk, A.K. (2008), Produc-line compeiion: cusomizaion vs proliferaion, Managemen Science, Vol. 54 No. 12, pp Invenory and financial performance 805

18 IJOPM 29,8 806 Nahm, A.Y., Vonderembse, M.A. and Kouferos, X.A. (2003), The impac of organizaional srucure on ime-based manufacuring and plan performance, Journal of Operaions Managemen, Vol. 21 No. 3, pp Naylor, J.B., Naim, M.M. and Berry, D. (1999), Leagiliy: inegraing he lean and agile manufacuring paradigms in he oal supply chain, Inernaional Journal of Producion Economics, Vol. 62 Nos 1/2, pp Neil, G. and O Hara, J. (1987), The inroducion of JIT ino a high echnology elecronics manufacuring environmen, Inernaional Journal of Operaions & Producion Managemen, Vol. 7 No. 4, pp Norris, D.M., Swenson, R.D. and Chu, Y. (1994), Jus-in-ime producion sysems: a survey of managers, Producion & Invenory Managemen Journal, Vol. 35 No. 2, pp Palepu, K., Peek, E., Bernard, V. and Healy, P. (2007), Business Analysis and Valuaion: Using Financial Saemens, Thomson Learning, London. Rajagopalan, S. and Malhora, A. (2001), Have US manufacuring invenories really decreased? An empirical sudy, Manufacuring and Service Operaions Managemen, Vol. 3 No. 1, pp Roumiansev, S. and Neessine, S. (2007), Wha can be learned from classical invenory models: a cross-indusry exploraory invesigaion, Manufacuring and Service Operaions Managemen, Vol. 9 No. 4, pp Sakakibara, S., Flynn, B.B., Schroeder, R.G. and Morris, W.T. (1997), The impac of jus in ime manufacuring and is infrasrucure on manufacuring performance, Managemen Science, Vol. 43 No. 9, pp Schmenner, R.W. (2001), Looking ahead by looking back: swif, even flow in he hisory of manufacuring, Producion and Operaions Managemen, Vol. 10 No. 1, pp Schmenner, R.W. and Swink, M.L. (1998), On heory in operaions managemen, Journal of Operaions Managemen, Vol. 17 No. 1, pp Shah, R. and Shin, H. (2007), Relaionships among informaion echnology, invenory, and profiabiliy: an invesigaion of level invariance using secor level daa, Journal of Operaions Managemen, Vol. 25 No. 4, pp Sine, W.D., Shane, S. and Di Gregorio, D. (2003), The halo effec and echnology licensing: he influence of insiuional presige on he licensing of universiy invenions, Managemen Science, Vol. 49 No. 4, pp Salk, G. Jr (1988), Time he nex source of compeiion advanage, Harvard Business Review, Vol. 66 No. 4, pp Suri, R. (1998), Quick Response Manufacuring, Produciviy Press, Porland, OR. Womack, J.P., Jones, D.T. and Roos, D. (1990), The Machine ha Changed he World, Rawson Associaes, New York, NY. Corresponding auhor Vedran Capkun can be conaced a: capkun@hec.fr To purchase reprins of his aricle please reprins@emeraldinsigh.com Or visi our web sie for furher deails:

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