DOI: 10.5061/dryad.sn02v6xcs
title: The impact of top management team tenure heterogeneity on declining firm's innovation efficiency

description: A firm maybe experiences a flourishing or declining period, and it also
 probably survives or even dies in future. Most firms have experienced
 decline in their development process. The impact of demand contraction and
 COVID-19 has caused more firms to face decline. Under the dilemma of
 resources reduction and recovery, the declining firm pays more and more
 attention to the efficient utilization of limited resources. It attempts
 to achieve turnaround through CEO substitution, adjustment of ownership
 concentration, innovation-oriented and other strategies. Based on Upper
 echelons theory and resource-based view, using the data of A-share listed
 manufacturing firms in Shanghai and Shenzhen from 2015 to 2019, the
 impacts of TMT tenure heterogeneity and ownership concentration on the
 innovation efficiency were investigated. The results show that the TMT
 tenure heterogeneity promotes the innovation efficiency of declining
 firms, while the relatively centralized ownership structure negatively
 moderates this effect. The robustness analysis of variable replacement and
 the solving of endogenous problem also further support this conclusion.
 This study not only enriches the application areas of Upper echelons
 theory, but also provides practical guideline for declining firms to
 replace top management members and to dilute equity in order to achieve
 recovery.
description: The data mainly comes from the annual data of Shanghai and
 Shenzhen A-share listed manufacturing firms from 2015 to 2019. Referring
 to Teixeira et al. (2019), firms that meet the following criteria are
 defined as declining firms: (1) ROA decreases for at least two consecutive
 years; (2) ROA is negative for at least three consecutive years. Firms
 with missing key indicators such as R&D expenditures and number of
 patents granted are excluded. The patent data are obtained from the CNRDS
 database, and the financial data are obtained from the CSMAR and WIND
 databases. Meanwhile, to ensure the comparability of samples, 534 firm
 observations are finally selected after PSM nearest-neighbour matching on
 a 1:1 no-put-back basis, of which 267 are declining firms and 267 are
 normal firms. The DEA-Malmquist index is calculated using Deap2.1.
 Finally, 2136 sample observations are obtained from 2016 to
 2019.
description: ### README: Variables #### Dependent variable Technological innovation
 efficiency (*Tfpch*): DEA-Malmquist Index by firm, 2016-2019 Compared with
 DEA model, Malmquist Index model can measure technological innovation
 efficiency in multiple periods. Our research uses Malmquist Index to
 express technological innovation efficiency. R&D input is the capital
 stock of R&D expenditure calculated by the perpetual inventory method
 and the number of R&D personnel of the firm in the current year.
 Considering the long patent granting cycle, the innovation output is
 selected from the firm's current year's business revenue and the
 number of patents granted in the lagging period. R&D capital stock:
 *K_it*=*K_(it-1)* *(1-δ_it )*+*Ι_it* (1) Base period capital stock:
 *K_0*=*I_0/(g+δ)* *K_it* is the R&D capital stock of firm *i* in year
 *t*. *Ι_it* is the actual R&D capital investment of firm *i* in year
 *t*, deflated using 2015 as the base period. *δ* is the depreciation rate
 and g is the average growth rate of R&D investment. Based on the
 existing research, *δ* is 15% (Hu et al., 2005). The price conversion
 index for R&D inputs is: 0.45*investment in fixed assets price index +
 0.55*consumer price index. Due to the reduction of R&D expenses by
 some declining firms, *g* is taken as a negative value. Therefore, when
 calculating the base period capital stock, firms with a true g value less
 than 0 are calculated as 0. #### Independent variable TMT tenure
 heterogeneity (*Ten*): Coefficient of variation The main measures of TMT
 tenure heterogeneity are the Herfindal-Hirschman (Niebuhr, 2010)
 coefficient and the coefficient of variation (Anderson et al., 2011).
 Considering that TMT tenure heterogeneity is a continuous variable, we
 choose the coefficient of variation to denote TMT tenure heterogeneity,
 with larger values indicating greater TMT tenure heterogeneity. The TMT
 members mainly include the chairman, (vice) president, (vice) general
 manager, assistant to the general manager, secretary of the board of
 directors, directors, supervisors, functional department directors and
 other managers (Khosravi et al., 2019; Lee et al., 2021). #### Moderator
 variable Ownership concentration (*Top1*): Shareholding ratio of the
 largest shareholder The proportion of shares held by the first largest
 shareholder is used to represent the ownership concentration within the
 firm (Zulfiqar and Hussain, 2020). #### Control variables Enterprise size
 (*Esize*): Ln (total assets at the end of the year) TMT size (*Tsize*): Ln
 (number of TMT+1):  Board size (*Dsize*): Ln (number of board members+1)
 Solvency (*Asse*t): Asset-liability ratio Growth ability (*Tobinq*): Tobin
 q Operational capability (*Growth*): Total asset turnover ratio
 Profitability (*Roa*): ROE Executive shareholding ratio (*ES*): Ratio of
 shares held by executives to total shares Subsidy intensity (*Sub*): Ratio
 of subsidy amount to operating revenue Capital intensity (*CI*): Ln (net
 fixed assets per capita) Proportion of state-owned shares (*State*): Ratio
 of state-owned shares to total shares Equity balances degree (*BS*): Sum
 of shareholdings of the second to tenth shareholders Age of firm
 (*Age*): Ln (time lag between inspection period and listing period) Nature
 of ownership (*Nature*): Dummy variable, state-owned firm=1; private
 firm=0 Industry (*Industry*): Dummy variable, 1-7 dummy variables based on
 2012 SEC industry classification Year (*Year*)