Knowledge, Skills and Productivity in UK Retailing

O. Bozkurt, J. Clegg, I. Grugulis, D. Anon Higon, S. Salis,N. Vasilakos and A. Williams

In collaboration with Bradford, Leeds and London Metropolitan Universities

Group 1: Case studies

Intra-Company Knowledge Transfers, Skills, and Productivity in UK Supermarkets

Jeremy Clegg, Irena Grugulis and Odul Bozkurt

Bradford and Leeds Universities

Primary Research Questions

1-) How do practitioners at various levels in UK supermarkets understand and measure “productivity”? How do they conceive of the relationship between “productivity” and “performance”?

2-) According to strategists and managers in UK supermarkets, what are the most important drivers of and impediments to productivity growth in their business today?

3-) What are the routes of dissemination of knowledge inside supermarkets, including that from foreign parents?

4-) What are the consequences of the efforts to improve productivity and performance on the organization of work and the knowledge-content of jobs in the sector?

5-) Does productivity in the sector rely on and bring about a low-skills equilibrium, and what might be the larger consequences of this for the UK economy?

In-Depth Case-Study Research in Major UK Supermarkets

Overall Research Progress

We have secured initial access into three major supermarket chains, and conducted initial interviews with Head Office representatives.

Two of these supermarkets are of similar size and market share, one of them a foreign-owned multinational, the other one a UK-owned non-multinational.

Fieldwork with the first supermarket chain started in July 2006. We have been granted extensive access for open-ended research here. General agreement has been reached with the second supermarket chain for similar level of access, and final negotiations are underway on confidentiality issues.

The third supermarket chain is much smaller in terms of size of operations and market share, but offers a unique combination of high-quality merchandise and service with high employee development, so we are interested in pursuing this case further after completion of work with the first two supermarkets.

Contacts have been established in sector forums, and multiple interviews have been conducted with key informants in the sector employed outside of supermarkets.

Case Study 1:

Research ActivitiesHead Office: 8 out of planned 10-12 interviews at Head Office completed– These include interviews with high

level executives in Business Improvement, Wage Planning, Recruitment, Training, Customer Service and Loss Prevention areas, as well as an expatriate expert from the MNE overseas headquarters.

3 day observation at induction event– including presentations by company CEO and head of Retail Operations, Customer Service and other high level company executives.

Store: Store 1, an example of a “healthy store”, has been selected after review of store performance

indicators and in consultation with Head Office contact. Introductory visit to and tour of Store 1 completed together with Head Office contact. 8 out of 10 planned interviews with managers have been completed. We have revised our initial

plans to now extend the management interviews to 15 out of about 20 managers in the average store of the chain.

Access has been obtained from two Department Managers for participant observation to be carried out with them as an employee; now scheduled for November-December 2006. These will include at least one stint in a department that is a “production site”.

20 interviews will be carried out with shopfloor workers in Store 1; certain groups (workers with long tenure, students, foreign-born etc.) have already been targeted and initial participants identified. Target date for completion of these interviews is Christmas 2006.

We are looking into the selection of Store 2, an example of a “difficult store”, with different performance scores on key indicators. This will allow for intra-firm comparison.

We have started the transcriptions and initial review of interviews carried out thus far.

Group 2: WERS dataset

Summary of our sub-project

Allan Williams & Sergio Salis

London Metropolitan University

Use the WERS 2004 to studythe relationship between..

1 - Intra-firm knowledge transfersand firm performance/productivity

Cannot be done now, except for single-establishment (plant) firms (see point 2). Only 19 single-establishment firms in retailing (out of 223 identified retailers), of which only one foreign owned. But may be possible to study intra-firm knowledge transfers later if we can link WERS and ARD (Virtual Lab) in order to identify firms (212 retail establishments agreed to link WERS with other datasets).

2 - Intra-establishment knowledge transfersand establishment performance/productivity

Current focus - We can control for whether establishments are domestic or foreign owned (47 out of 223 establishments in retailing), and the extent of the ownership (50%, > 50% or 100%). We can alsocontrol for variables reflecting knowledge transfers from outside the firms (e.g. external consultancy or professional advice).

Intra-establishment knowledge transfers and performance/productivity: Methodology

INDIRECTLY (knowledge transfers cannot be directly observed) -By assessing whether some specific HR practices are strongly correlated with productivity/performance.

Specific HR practices are those that, in theory, facilitate knowledge transfers within the establishment, especially knowledge-based interactions amongst individuals. Focus=correlation. Causality could be studied (checks are needed!) by using the panel component of WERS (1998-2004) or merging WERS 2004 and WERS 1998.

Initially, focus on subjective measures (managers’ perceptions). Objective measures of productivity can be derived from the Financial Performance Questionnaire of WERS 2004 (available for a sub-sample of establishments in the ONS Virtual Lab).

HR practices enhancing knowledge transfers within establishments

Aim to group according to the following criteria:

- HR practices likely to increase the number of interactions among individuals (typical approach).

- HR practices favouring bi-directional interactions among individuals (e.g. meetings and teams, after controlling that no single leader monopolises or unilaterally directs these).

- HR practices increasing the efficiency of interactions among individuals (practices decreasing the cost/time needed for interactions).

- HR practices allowing for the interactions to be effective (stress on practices favouring absorption capability, i.e. human capital and skills).

Aim to construct (up to) 4 indicators (one for each criterion above if possible) of HR practices and regress performance measures against them.

Group 3: ARD and AFDI Datasets

The Role of MNEs and FDI spillovers in the UK retail Sector

Dolores Anon Higon and Nicholas V. Vasilakos

Aston University

MNCs in UK Retailing

Share (%) of Employment as FTE in UK Retailing (SIC92: 52)Growth

1997 1998 1999 2000 2001 2002 2003 RateUK MNE 27.4 25.5 34.0 27.1 30.9 33.0 33.4 3.3%Foreign MNE 2.5 3.3 4.7 10.5 10.4 9.2 11.4 25.3%Local Non-MNE 70.0 61.2 61.3 62.4 58.6 57.8 55.2 -4.0%Source: Office for National Statistics (ONS), authors calculations using ARD establishment-level weighted sample data, and Annual Inquiry into Foreign Direct Investment

Table 1: Percenatge of employment by ownership type in 2001. Source Griffith et al. (2004)

British Only British Owned Foreign-Owned

Services 77.3 14.0 8.4

Catering 76.9 14.7 8.4Retail Trade 57.0 34.9 8.2Wholesale 65.1 13.2 21.6

Multinationals

How much better are MNEs?

Model 1 Model 2 MNE UK_MNE USMNE RoWMNE

Employment (FTE) 0.824*** 1.496*** 0.483** 0.294*** (0.089) (0.153) (0.190) (0.080)

Average Salaries (FTE) 0.100*** 0.002 0.213*** 0.453***

(0.028) (0.041) (0.075) (0.042) Capital-Labour (K/L) 0.578*** 0.483*** 0.710*** 0.628***

(0.044) (0.056) (0.082) (0.071) LP(VA/FTE) 0.247*** 0.304*** 0.473*** 0.126**

(0.038) (0.049) (0.101) (0.061) TFP(VA) by LevPet 0.109*** 0.255*** 0.252** -0.079

(0.025) (0.042) (0.110) (0.101) TFP(GO) by LevPet 0.050*** 0.090*** 0.087** 0.001

(0.016) (0.019) (0.039) (0.001) TFP(GO)- 0.045*** 0.068*** 0.066** 0.013 Superlative index (0.010) (0.011) (0.026) (0.016)

Source: authors’ calculations using ONS’ ARD

RESULTS:

On average, MNEs pay higher average salaries; however, when we differentiate in terms of origin of ownership, just foreign MNEs pay higher. These differences might indicate a skill bias towards high skilled

workers in the labour force of foreign MNEs. UK_MNEs hire more employees than foreign MNEs; all

MNEs hire more than local non-MNE firms when controlling for age & size just UKMNEs use more PT UK_MNEs hire more FT than foreign MNEs; all MNEs hire more FT than rest

of indigenous firms.

MNEs are more productive than non-MNEs independently of the productivity measure. UK_MNEs are as productive as US_MNEs in terms of LP and TFP RoW MNE are not significantly more productive than local non_MNE

firms, except in terms of LP

To what extent FDI benefits local UK retailers?

-Restrict sample to domestic firm

-We look at intra-industry & regional spillovers

-Traditional Cobb-Douglas production function, correcting for endogeneity:

-Levinsohn & Petrin, when dependent varible is log(TFP)

-GMM method, when dependent variable is log(go)

--Control for absorptive capacity: using superlative index of Caves et al for the TFP (Girma & Gorg, 2005)

1 2 ( 1) 3 ( 1) 4log log ( * )ijrt ijrt ijr t ijr t ijrt ijrtP X Spill ABC Spill Z

Empirical Results

Total Sample Single PlantsRobust OLS Robust RobustStd. Error Coeff Std. Err Std. Error0.118 0.510** 0.205 0.1370.064 0.284** 0.113 0.0820.100 0.527*** 0.14 0.1331.140 4.255*** 1.562 1.4890.977 3.502*** 1.006 1.329

uk_mne 0.010 0.062 0.049 0.01HHI 0.345 -4.89 0.610 0.391

No. of Obs. 4236 1218 3018yes

Multiplants

Sectoral Dummies yes yes

0.195***spilinR(t-1)abcs(t-1) 0.737***

0.168**0.869***

Time Dummies yes yesRegional Dummies yes yes

yesyes

0.033*** 0.026**-0.502 -0.354

abcs(t-1)*spillin3(t-1) 1.905* 0.274abcs(t-1)*spillinR(t-1) 3.014*** 2.842**

Coeff Coeffspilin3(t-1) 0.072 -0.198

Dependent variable: log(TFP) using Levinsohn & Petrin

OLS OLS

Impact of inward intra-industry & regional spillovers (1997-2003)

Source: authors’ calculations using ONS’ ARD merged with AFDI

Empirical Results

Dependent variable: log(go)GMMCoeff Std. Error

log(emplf) 0.111*** 0.025log(capital) 0.138*** 0.020log(materials) 0.725*** 0.030spilin3(t-1) -0.156* 0.092spilinR(t-1) 0.201*** 0.051abc(t-1) 0.868*** 0.087abc(t-1)*spillin3(t-1) 0.363 0.947abc(t-1)*spillinR(t-1) 3.064*** 0.801UK_MNE 0.013 0.024HHI -0.453* 0.245Time Dummies yesRegional Dummies yesSectoral Dummies yesNumber observation 4236

Source: authors’ calculations using ONS’ ARD merged with AFDI

Results

The results using both approaches, find positive regional spillovers from FDI to UK retailers

The intra-industry results are less clear: Results show that single plants are the ones who

benefit form intra-industry spillovers form FDI.

Retailers benefit more from spillovers as closer they are from the technological leader

Future Plans

Write draft paper Look at outward spillovers, given the importance

of UK_MNEs in retailing Look at the importance of ICT intensity (data on

investment in software-but not for all firms). Split sample according to ICT intensity and see if the impact of spillovers differs…we have done so, but data on software investment is of poor quality