Phases 1 & 2: Quantitative Data Collection and Analysis

To examine the impact of Supply Chain, operations and Value Chain on business performance, seven primary variables are collected from the investment research database Morningstar:

(1) Gross Margin is a company's total revenue minus the cost of goods sold (COGS), divided by the total revenue, expressed as a percentage. Therefore, the gross margin represents the percentage of total revenue that the company retains from selling goods, after incurring the direct costs associated with producing the goods and services sold. David et al. (2002) provide empirical evidence that gross margin is a statistically significant predictor to identify a differentiation advantage (Fritz, 2008, pp. 111-112). A high gross margin indicates revenue growth, which is a positive factor only if cost of sales remains in the same proportion of lower than in previous periods; it is used to compare company growth (Arnold, 2009).

(2) Market Capitalisation and Market Cap Growth Rate: market capitalisation is calculated by multiplying a company's shares outstanding by the current market price of one share. Therefore, market capitalisation growth indicates an increase in the value of a company,

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as perceived by the financial market, which is liable to fluctuation as it is subjectively assessed (Arnold, 2009; Pilbeam, 2005).

(3) Revenue Growth indicates the increase or decrease in revenues over time and, therefore, measures how quickly a business is expanding, its growth rate, and indicates the successful increase in demand for the company’s products but does not necessarily suggest profit trends (Arnold, 2009)

(4) Payables Period, also referred to as Days Payable Outstanding (DPO), is calculated using the company’s financial statements analysis, and is calculated, by taking the accounts payable to creditors figure divided by the costs of sales, multiplied by 365 days. Therefore, this measure exhibits the degree to which the company makes use of supplier credit; an increase in the number creditors is positive in so far as the firm has the potential for acquiring extra interest revenue because the cash stays in its bank for longer (Arnold, 2009; Wills and Robertson, 1991).

(5) Stock Turnover is the ratio measured in days and determines the number of times a company's stock is sold and replaced over a specified period, usually one year. Therefore, the stock turnover ratio indicates the efficiency of a company in controlling its inventory, and is calculated as costs of goods sold (COGS) divided by inventory, multiplied by 365 days. The more effectively the Supply Chain is synchronised with customer demand, the higher the stock turnover (Harrison et al., 2005, p. 232). Therefore, a company with a more efficient Supply Chain shows a lower number of stock turnover days than one with a high number of days, since the number of days indicates the number of days the company could meet consumer demand without replenishing stock (Wills & Robertson, 1991; Bamber & Parry, 2014). (6) The Cash Conversion Cycle is a metric that expresses the length of time

in days, which a company takes to convert resource inputs into cash flows. It is calculated as follows:

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where, DIO is days of inventory outstanding, DSO is days of sales outstanding, and DPO is days payable outstanding. The cash conversion cycle is an indicator of the length of time for which working capital elements in the Supply Chain must be financed (Baltes, 2015, p. 97). Therefore, the degree of efficiency of the Supply Chain generally has a direct impact on the cash conversion cycle (Baltes, 2015, p. 97). The lower the value of the cash conversion cycle, the greater the company’s efficiency and management effectiveness since it represents the time lapse between an outgoing payment made to supplier and receipt of the customer’s invoice payment (Bamber & Parry, 2014). Cash flow monitoring is especially vitals for companies in the retail industry owing to the seasonal fluctuations it experiences (Havell & Levine, 1996)

(7) The Return On Invested Capital (ROIC) measures how effectively a company allocates its financial capital to generate returns, and how profitably the invested capital has been allocated; the higher the value, the more effectively capital has been utilised for the intended purpose (Arnold, 2009).

The relationship between cash conversion cycle, asset turnover and stock days, as a measure that examines the efficiency of a company’s Supply Chain, was considered by Sople (2012), (see Figure 20).

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Figure 20: Relationship of Measures in the Supply Chain

Source: Sople (2012, p. 386)

The asset turnover measures the amount of revenue generated per dollar of assets and is an indicator of the efficiency, with which a company is deploying its assets. However, category assets are directly linked to stock turnover, fixed asset turnover, accounts payable to creditors, accounts receivable from debtors and other assets, so that the measure is very inaccurate. According to Sople (2012, p. 386), the cash conversion cycle, referred to in Figure 18 as the cash-to-cash cycle time, has a direct impact on the asset turnover, which consequently affects the stock/inventory days. Therefore, this thesis ignores the asset turnover, in the context of the descriptive analysis, and uses the original measures only, in the form of stock turnover and cash conversion cycle, to examine the Value Chain and Supply Chain efficiencies. This measure allows a direct inference to be made on the overall efficiency in the management of all assets, but does not enable a direct conclusion to be made regarding the impact on Supply Chain and Value Chain efficiency with regard to firm performance. The asset turnover ratio is introduced as a controlling variable only in the case of statistical tests, which are executed in the second part of this analysis,

The research design comprises of the following three steps:

Firstly, the total sample is examined by the means of descriptive analysis and bivariate analysis, based on all primary data variables, that is, all financial data from the investment research database, Morningstar. In the case of the descriptive analysis, the objective is to compare the total sample, and to

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identify any abnormalities, which lead to bivariate tests of distinct variables. In the case of bivariate analysis, all primary data variables are tested simultaneously, in order to identify possible relationships between firm performance variables, ROIC, market capitalisation and revenue, as dependent variables, and the set of independent variables relating to the total sample and, therefore, on the assumption that the sample is representative of the whole fashion industry.

Statistical analysis is then conducted by clustering the total sample in terms of inventory turnover and gross margin, in relation to the total sample average of both variables. Therefore, the subsets derived are coded according to their position in the matrix, as slow turnover/low margin companies and fast turnover/high margin companies.

The companies that also show outstanding performance in the descriptive analysis are compared with each other, to facilitate identification of statistical relationships, which distinguish some companies from all others, particularly in terms of overall performance and Supply Chain performance.

However, these steps in the analysis are not implemented strictly in the order given above, but developed in the form of meaningful presentation of the results, in the framework of a gradually developed argument, based on the results of the statistical analysis.